Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling

NASA Astrophysics Data System (ADS)

Baatz, Roland; Sullivan, Pamela L.; Li, Li; Weintraub, Samantha R.; Loescher, Henry W.; Mirtl, Michael; Groffman, Peter M.; Wall, Diana H.; Young, Michael; White, Tim; Wen, Hang; Zacharias, Steffen; Kühn, Ingolf; Tang, Jianwu; Gaillardet, Jérôme; Braud, Isabelle; Flores, Alejandro N.; Kumar, Praveen; Lin, Henry; Ghezzehei, Teamrat; Jones, Julia; Gholz, Henry L.; Vereecken, Harry; Van Looy, Kris

2018-05-01

Advancing our understanding of Earth system dynamics (ESD) depends on the development of models and other analytical tools that apply physical, biological, and chemical data. This ambition to increase understanding and develop models of ESD based on site observations was the stimulus for creating the networks of Long-Term Ecological Research (LTER), Critical Zone Observatories (CZOs), and others. We organized a survey, the results of which identified pressing gaps in data availability from these networks, in particular for the future development and evaluation of models that represent ESD processes, and provide insights for improvement in both data collection and model integration. From this survey overview of data applications in the context of LTER and CZO research, we identified three challenges: (1) widen application of terrestrial observation network data in Earth system modelling, (2) develop integrated Earth system models that incorporate process representation and data of multiple disciplines, and (3) identify complementarity in measured variables and spatial extent, and promoting synergies in the existing observational networks. These challenges lead to perspectives and recommendations for an improved dialogue between the observation networks and the ESD modelling community, including co-location of sites in the existing networks and further formalizing these recommendations among these communities. Developing these synergies will enable cross-site and cross-network comparison and synthesis studies, which will help produce insights around organizing principles, classifications, and general rules of coupling processes with environmental conditions.

Laboratory observations of biocide efficiency against Legionella in model cooling tower systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, W.M.; Eccles, J.; Fricker, C.

1999-07-01

The efficacy of specific oxidizing and non-oxidizing biocides was examined using a model cooling system inoculated with a microcosm containing an environmental isolate of Legionella pneumophila. The microcosm was prepared in a two-stage chemostat, which provided a consistent source of microbiological inoculum for the study. The microcosm consisted of both sessile (within biofilms) and planktonic Legionella in association with other microorganisms, including Pseudomonas species and cyst-forming ameobae. A procedure was established to successfully transfer the chemostat grown inoculum to the model cooling system and establish both sessile and planktonic forms of Legionella in the model cooling system. The greatest biocidalmore » effect for all of the biocides was observed immediately after dosing. This effect was relatively short-lived even for the slow acting biocides such isothiazolin (as 8 ppm active) where an effect was only observed over the first 12 hours. The faster acting biocides, DBNPA (as 8 ppm active) and gluteraldehyde (as 27 ppm active), did initially reduce Legionella populations but did not totally eliminate Legionella or provide lasting control. Chlorine and bromine (as 0.5--1.5 ppm free halogen), and ozone (as 0.1--0.5 ppm free reserve) reduced and controlled Legionella populations so long as a free reserve of oxidant was maintained. Legionella recovered quickly after biocide dosing, reestablishing similar levels to those observed before dosing.« less

Observability and synchronization of neuron models.

PubMed

Aguirre, Luis A; Portes, Leonardo L; Letellier, Christophe

2017-10-01

Observability is the property that enables recovering the state of a dynamical system from a reduced number of measured variables. In high-dimensional systems, it is therefore important to make sure that the variable recorded to perform the analysis conveys good observability of the system dynamics. The observability of a network of neuron models depends nontrivially on the observability of the node dynamics and on the topology of the network. The aim of this paper is twofold. First, to perform a study of observability using four well-known neuron models by computing three different observability coefficients. This not only clarifies observability properties of the models but also shows the limitations of applicability of each type of coefficients in the context of such models. Second, to study the emergence of phase synchronization in networks composed of neuron models. This is done performing multivariate singular spectrum analysis which, to the best of the authors' knowledge, has not been used in the context of networks of neuron models. It is shown that it is possible to detect phase synchronization: (i) without having to measure all the state variables, but only one (that provides greatest observability) from each node and (ii) without having to estimate the phase.

A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

NASA Astrophysics Data System (ADS)

Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

2011-12-01

Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples

Earth Observing System (EOS) Communication (Ecom) Modeling, Analysis, and Testbed (EMAT) activiy

NASA Technical Reports Server (NTRS)

Desai, Vishal

1994-01-01

This paper describes the Earth Observing System (EOS) Communication (Ecom) Modeling, Analysis, and Testbed (EMAT) activity performed by Code 540 in support of the Ecom project. Ecom is the ground-to-ground data transport system for operational EOS traffic. The National Aeronautic and Space Administration (NASA) Communications (Nascom) Division, Code 540, is responsible for implementing Ecom. Ecom interfaces with various systems to transport EOS forward link commands, return link telemetry, and science payload data. To understand the complexities surrounding the design and implementation of Ecom, it is necessary that sufficient testbedding, modeling, and analysis be conducted prior to the design phase. These activities, when grouped, are referred to as the EMAT activity. This paper describes work accomplished to date in each of the three major EMAT activities: modeling, analysis, and testbedding.

Improved Analysis of Earth System Models and Observations using Simple Climate Models

NASA Astrophysics Data System (ADS)

Nadiga, B. T.; Urban, N. M.

2016-12-01

Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using

A net-centric system of services model for the Integrated Earth Observation System (IEOS) and the Integrated Ocean Observing System (IOOS)

NASA Astrophysics Data System (ADS)

Ardanuy, Philip; Bensman, Ed; Bergen, Bill; Chen, Bob; Griffith, Frank; Sutton, Cary; Hood, Carroll; Ritchie, Adrian; Tarro, Andre

2006-08-01

This paper considers an evolved technique for significantly enhanced enterprise-level data processing, reprocessing, archival, dissemination, and utilization. There is today a robust working paradigm established with the Advanced Weather Interactive Processing System (AWIPS)-NOAA/NWS's information integration and fusion capability. This process model extends vertically, and seamlessly, from environmental sensing through the direct delivery of societal benefit. NWS, via AWIPS, is the primary source of weather forecast and warning information in the nation. AWIPS is the tested and proven "the nerve center of operations" at all 122 NWS Weather Forecast Offices (WFOs) and 13 River Forecast Centers (RFCs). However, additional line organizations whose role in satisfying NOAA's five mission goals (ecosystems, climate, weather & water, commerce & transportation, and mission support) in multiple program areas might be facilitated through utilization of AWIPS-like functionalities, including the National Marine Fisheries Service (NMFS); National Environmental Satellite, Data, and Information Service (NESDIS); Office of Oceanic & Atmospheric Research (OAR); and the National Ocean Service (NOS). In addition to NOAA's mission goals, there are nine diverse, recommended, and important societal benefit areas in the US Integrated Earth Observation System (IEOS). This paper shows how the satisfaction of this suite of goals and benefit areas can be optimized by leveraging several key ingredients: (1) the evolution of AWIPS towards a net-centric system of services concept of operations; (2) infusion of technologies and concepts from pathfinder systems; (3) the development of new observing systems targeted at deliberate, and not just serendipitous, societal benefit; and (4) the diverse, nested local, regional, national, and international scales of the different benefits and goal areas, and their interoperability and interplay across the system of systems.

Model Uncertainty Quantification Methods For Data Assimilation In Partially Observed Multi-Scale Systems

NASA Astrophysics Data System (ADS)

Pathiraja, S. D.; van Leeuwen, P. J.

2017-12-01

Model Uncertainty Quantification remains one of the central challenges of effective Data Assimilation (DA) in complex partially observed non-linear systems. Stochastic parameterization methods have been proposed in recent years as a means of capturing the uncertainty associated with unresolved sub-grid scale processes. Such approaches generally require some knowledge of the true sub-grid scale process or rely on full observations of the larger scale resolved process. We present a methodology for estimating the statistics of sub-grid scale processes using only partial observations of the resolved process. It finds model error realisations over a training period by minimizing their conditional variance, constrained by available observations. Special is that these realisations are binned conditioned on the previous model state during the minimization process, allowing for the recovery of complex error structures. The efficacy of the approach is demonstrated through numerical experiments on the multi-scale Lorenz 96' model. We consider different parameterizations of the model with both small and large time scale separations between slow and fast variables. Results are compared to two existing methods for accounting for model uncertainty in DA and shown to provide improved analyses and forecasts.

Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

PubMed

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.

The Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Kester, Dana

1992-01-01

A Global Ocean Observing System (GOOS) should be established now with international coordination (1) to address issues of global change, (2) to implement operational ENSO forecasts, (3) to provide the data required to apply global ocean circulation models, and (4) to extract the greatest value from the one billion dollar investment over the next ten years in ocean remote sensing by the world's space agencies. The objectives of GOOS will focus on climatic and oceanic predictions, on assessing coastal pollution, and in determining the sustainability of living marine resources and ecosystems. GOOS will be a complete system including satellite observations, in situ observations, numerical modeling of ocean processes, and data exchange and management. A series of practical and economic benefits will be derived from the information generated by GOOS. In addition to the marine science community, these benefits will be realized by the energy industries of the world, and by the world's fisheries. The basic oceanic variables that are required to meet the oceanic and predictability objectives of GOOS include wind velocity over the ocean, sea surface temperature and salinity, oceanic profiles of temperature and salinity, surface current, sea level, the extent and thickness of sea ice, the partial pressure of CO2 in surface waters, and the chlorophyll concentration of surface waters. Ocean circulation models and coupled ocean-atmosphere models can be used to evaluate observing system design, to assimilate diverse data sets from in situ and remotely sensed observations, and ultimately to predict future states of the system. The volume of ocean data will increase enormously over the next decade as new satellite systems are launched and as complementary in situ measuring systems are deployed. These data must be transmitted, quality controlled, exchanged, analyzed, and archived with the best state-of-the-art computational methods.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1984-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The full state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system rmain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1985-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The fulll state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system remain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Polarimetry of Solar System Objects: Observations vs. Models

NASA Astrophysics Data System (ADS)

Yanamandra-Fisher, P. A.

2014-04-01

results of main belt comets, asteroids with ring system, lunar studies, planned exploration of planetary satellites that may harbour sub-surface oceans, there is increasing need to include polarimetric (linear, circular and differential) as an integral observing mode of instruments and facilities. For laboratory measurements, there is a need to identify simulants that mimic the polarimetric behaviour of solar system small bodies and measure their polarimetric behavior as function of various physical process they are subject to and have undergone radiation changes of their surfaces. Therefore, inclusion of polarimetric remote sensing and development of spectropolarimeters for groundbased facilities and instruments on space missions is needed, with similar maturation of vector radiative transfer models and related laboratory measurements.

PanEurasian Experiment (PEEX): Modelling Platform for Earth System Observations and Forecasting

NASA Astrophysics Data System (ADS)

Baklanov, Alexander; Mahura, Alexander; Penenko, Vladimir; Zilitinkevich, Sergej; Kulmala, Markku

2014-05-01

As the part of the PEEX initiative, for the purpose of supporting the PEEX observational system and answering on the PEEX scientific questions, a hierarchy/ framework of modern multi-scale models for different elements of the Earth System integrated with the observation system is needed. One of the acute topics in the international debate on land-atmosphere interactions in relation to global change is the Earth System Modeling (ESM). The question is whether the ESM components actually represent how the Earth is functioning. The ESMs consist of equations describing the processes in the atmosphere, ocean, cryosphere, terrestrial and marine biosphere. ESMs are the best tools for analyzing the effect of different environmental changes on future climate or for studying the role of whole processes in the Earth System. These types of analysis and prediction of the future change are especially important in the Arctic latitudes, where climate change is proceeding fastest and where near-surface warming has been about twice the global average during the recent decades. The processes, and hence parameterization, in ESMs are still based on insufficient knowledge of physical, chemical and biological mechanisms involved in the climate system and the resolution of known processes is insufficient. Global scale modeling of land-atmosphere-ocean interactions using ESMs provides a way to explore the influence of spatial and temporal variation in the activities of land system and on climate. There is a lack, however, ways to forward a necessary process understanding effectively to ESMs and to link all this to the decision-making process. Arctic-boreal geographical domain plays significant role in terms of green-house gases and anthropogenic emissions and as an aerosol source area in the Earth System. The PEEX Modelling Platform (PEEX-MP) is characterized by: • An ensemble approach with the integration of modelling results from different models/ countries etc.; • A hierarchy of

A model for gravity-wave spectra observed by Doppler sounding systems

NASA Technical Reports Server (NTRS)

Vanzandt, T. E.

1986-01-01

A model for Mesosphere - Stratosphere - Troposphere (MST) radar spectra is developed following the formalism presented by Pinkel (1981). Expressions for the one-dimensional spectra of radial velocity versus frequency and versus radial wave number are presented. Their dependence on the parameters of the gravity-wave spectrum and on the experimental parameters, radar zenith angle and averaging time are described and the conditions for critical tests of the gravity-wave hypothesis are discussed. The model spectra is compared with spectra observed in the Arctic summer mesosphere by the Poker Flat radar. This model applies to any monostatic Doppler sounding system, including MST radar, Doppler lidar and Doppler sonar in the atmosphere, and Doppler sonar in the ocean.

Observationally-based Metrics of Ocean Carbon and Biogeochemical Variables are Essential for Evaluating Earth System Model Projections

NASA Astrophysics Data System (ADS)

Russell, J. L.; Sarmiento, J. L.

2017-12-01

The Southern Ocean is central to the climate's response to increasing levels of atmospheric greenhouse gases as it ventilates a large fraction of the global ocean volume. Global coupled climate models and earth system models, however, vary widely in their simulations of the Southern Ocean and its role in, and response to, the ongoing anthropogenic forcing. Due to its complex water-mass structure and dynamics, Southern Ocean carbon and heat uptake depend on a combination of winds, eddies, mixing, buoyancy fluxes and topography. Understanding how the ocean carries heat and carbon into its interior and how the observed wind changes are affecting this uptake is essential to accurately projecting transient climate sensitivity. Observationally-based metrics are critical for discerning processes and mechanisms, and for validating and comparing climate models. As the community shifts toward Earth system models with explicit carbon simulations, more direct observations of important biogeochemical parameters, like those obtained from the biogeochemically-sensored floats that are part of the Southern Ocean Carbon and Climate Observations and Modeling project, are essential. One goal of future observing systems should be to create observationally-based benchmarks that will lead to reducing uncertainties in climate projections, and especially uncertainties related to oceanic heat and carbon uptake.

Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Rienecker, Michele M.; Balmaseda, Magdalena; Awaji, Toshiyuki; Barnier, Bernard; Behringer, David; Bell, Mike; Bourassa, Mark; Brasseur, Pierre; Breivik, Lars-Anders; Carton, James;

Classification framework for partially observed dynamical systems

NASA Astrophysics Data System (ADS)

Shen, Yuan; Tino, Peter; Tsaneva-Atanasova, Krasimira

2017-04-01

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent individual data items, we employ posterior distributions over model parameters, thus taking into account in a principled manner the uncertainty due to both the generative (observational and/or dynamic noise) and observation (sampling in time) processes. We evaluate the framework on two test beds: a biological pathway model and a stochastic double-well system. Crucially, we show that the classification performance is not impaired when the model structure used for inferring posterior distributions is much more simple than the observation-generating model structure, provided the reduced-complexity inferential model structure captures the essential characteristics needed for the given classification task.

Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model.

PubMed

Nielsen, J Eric; Pawson, Steven; Molod, Andrea; Auer, Benjamin; da Silva, Arlindo M; Douglass, Anne R; Duncan, Bryan; Liang, Qing; Manyin, Michael; Oman, Luke D; Putman, William; Strahan, Susan E; Wargan, Krzysztof

2017-12-01

NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM), and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near-real-time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This paper describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)-based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided.

Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model

PubMed Central

Pawson, Steven; Molod, Andrea; Auer, Benjamin; da Silva, Arlindo M.; Douglass, Anne R.; Duncan, Bryan; Liang, Qing; Manyin, Michael; Oman, Luke D.; Putman, William; Strahan, Susan E.; Wargan, Krzysztof

2017-01-01

Abstract NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM), and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near‐real‐time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This paper describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)‐based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided. PMID:29497478

Constraining Earth System Models in the Tropics with Multiple Satellite Observations

NASA Astrophysics Data System (ADS)

Shi, M.; Liu, J.; Saatchi, S. S.; Chan, S.; Yu, Y.; Zhao, M.

2016-12-01

Because of the impacts of cloud and atmospheric aerosol on spectral observations and the saturation of spectral observations over dense forests, the current spectral observations (e.g., Moderate Resolution Imaging Spectroradiometer) have large uncertainties in the tropics. Nevertheless, the backscatter observations from the SeaWinds Scatterometer onboard QuikSCAT (QSCAT) are sensitive to the variations of canopy water content and structure of forest canopy, and are not affected by clouds and atmospheric aerosols. In addition, the lack of sensitivity of the Soil Moisture Active Passive (SMAP) Level 1C brightness temperature (TB) to soil moisture under dense forest canopies (e.g., forests in tropics) makes the SMAP TB data a direct indicator of canopy properties. In this study, we use a variety of new satellite observations, including the QSCAT backscatter observations, the Gravity Recovery and Climate Experiment (GRACE) satellite's observed temporal gravity field variations, and the SMAP Level 1C TB, to constrain the carbon (C) cycle simulated by the Community Land Model version 4.5 BGC (CLM4.5) for the 2005 Amazonia drought and 2015 El Nino. Our results show that the leaf C pool size simulated by CLM4.5 decreases dramatically in southwest Amazonia in the 2005 drought, and recovers slowly afterward (after about 3 years). This result is consistent with the long-term C-recovery after the 2005 Amazonia drought observed by QSCAT. The slow C pool recovery is associated with large fire disturbance and the slow water storage recovery simulated by CLM4.5 and observed by GRACE. We will also discuss the impact of the 2015 El Nino on the tropical C dynamics constrained by SMAP Level 1C data. This study represents an innovative way of using satellite microwave observations to constrain C cycle in an Earth system model.

Graphics Processing Units (GPU) and the Goddard Earth Observing System atmospheric model (GEOS-5): Implementation and Potential Applications

NASA Technical Reports Server (NTRS)

Putnam, William M.

2011-01-01

Earth system models like the Goddard Earth Observing System model (GEOS-5) have been pushing the limits of large clusters of multi-core microprocessors, producing breath-taking fidelity in resolving cloud systems at a global scale. GPU computing presents an opportunity for improving the efficiency of these leading edge models. A GPU implementation of GEOS-5 will facilitate the use of cloud-system resolving resolutions in data assimilation and weather prediction, at resolutions near 3.5 km, improving our ability to extract detailed information from high-resolution satellite observations and ultimately produce better weather and climate predictions

Using Combined Marine Spatial Planning Tools and Observing System Experiments to define Gaps in the Emerging European Ocean Observing System.

NASA Astrophysics Data System (ADS)

Nolan, G.; Pinardi, N.; Vukicevic, T.; Le Traon, P. Y.; Fernandez, V.

2016-02-01

Ocean observations are critical to providing accurate ocean forecasts that support operational decision making in European open and coastal seas. Observations are available in many forms from Fixed platforms e.g. Moored Buoys and tide gauges, underway measurements from Ferrybox systems, High Frequency radars and more recently from underwater Gliders and profiling floats. Observing System Simulation Experiments have been conducted to examine the relative contribution of each type of platform to an improvement in our ability to accurately forecast the future state of the ocean with HF radar and Gliders showing particular promise in improving model skill. There is considerable demand for ecosystem products and services from today's ocean observing system and biogeochemical observations are still relatively sparse particularly in coastal and shelf seas. There is a need to widen the techniques used to assess the fitness for purpose and gaps in the ocean observing system. As well as Observing System Simulation Experiments that quantify the effect of observations on the overall model skill we present a gap analysis based on (1) Examining where high model skill is required based on a marine spatial planning analysis of European seas i.e where does activity take place that requires more accurate forecasts? and (2) assessing gaps based on the capacity of the observing system to answer key societal challenges e.g. site suitability for aquaculture and ocean energy, oil spill response and contextual oceanographic products for fisheries and ecosystems. The broad based analysis will inform the development of the proposed European Ocean Observing System as a contribution to the Global Ocean Observing System (GOOS).

Cross-compartment evaluation of a fully-coupled hydrometeorological modeling system using comprehensive observation data

NASA Astrophysics Data System (ADS)

Fersch, Benjamin; Senatore, Alfonso; Kunstmann, Harald

2017-04-01

Fully-coupled hydrometeorological modeling enables investigations about the complex and often non-linear exchange mechanisms among subsurface, land, and atmosphere with respect to water and energy fluxes. The consideration of lateral redistribution of surface and subsurface water in such modeling systems is a crucial enhancement, allowing for a better representation of surface spatial patterns and providing also channel discharge predictions. However, the evaluation of fully-coupled simulations is difficult since the amount of physical detail along with feedback mechanisms leads to high degrees of freedom. Therefore, comprehensive observation data is required to obtain meaningful model configurations. We present a case study for a medium-sized river catchment in southern Germany that includes the calibration of the stand-alone and the evaluation of the fully-coupled WRF-Hydro modeling system with a horizontal resolution of 1 x 1 km2, for the period June to August 2015. ECMWF ERA-Interim reanalysis is used for model driving. Land-surface processes are represented by the Noah-MP land surface model. Land-cover is described by the EU CORINE data set. Observations for model evaluation are obtained from the TERENO Pre-Alpine observatory (http://www.imk-ifu.kit.edu/tereno.php) and are complemented by further measurements from the ScaleX campaign (http://scalex.imk-ifu.kit.edu) such as atmospheric profiles obtained from radiometer sounding and airborne systems as well as soil moisture and -temperature networks. We show how well water budgets and heat-fluxes are being reproduced by the stand-alone WRF, the stand-alone WRF-Hydro and the fully-coupled WRF-Hydro model.

A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system

USGS Publications Warehouse

Tiedeman, Claire; Ely, D. Matthew; Hill, Mary C.; O'Brien, Grady M.

2004-01-01

We develop a new observation‐prediction (OPR) statistic for evaluating the importance of system state observations to model predictions. The OPR statistic measures the change in prediction uncertainty produced when an observation is added to or removed from an existing monitoring network, and it can be used to guide refinement and enhancement of the network. Prediction uncertainty is approximated using a first‐order second‐moment method. We apply the OPR statistic to a model of the Death Valley regional groundwater flow system (DVRFS) to evaluate the importance of existing and potential hydraulic head observations to predicted advective transport paths in the saturated zone underlying Yucca Mountain and underground testing areas on the Nevada Test Site. Important existing observations tend to be far from the predicted paths, and many unimportant observations are in areas of high observation density. These results can be used to select locations at which increased observation accuracy would be beneficial and locations that could be removed from the network. Important potential observations are mostly in areas of high hydraulic gradient far from the paths. Results for both existing and potential observations are related to the flow system dynamics and coarse parameter zonation in the DVRFS model. If system properties in different locations are as similar as the zonation assumes, then the OPR results illustrate a data collection opportunity whereby observations in distant, high‐gradient areas can provide information about properties in flatter‐gradient areas near the paths. If this similarity is suspect, then the analysis produces a different type of data collection opportunity involving testing of model assumptions critical to the OPR results.

Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability

NASA Astrophysics Data System (ADS)

Dee, S. G.; Parsons, L. A.; Loope, G. R.; Overpeck, J. T.; Ault, T. R.; Emile-Geay, J.

2017-10-01

The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled ;pseudoproxies; exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate

Earth Observing System (EOS) Snow and Ice Products for Observation and Modeling

NASA Technical Reports Server (NTRS)

Hall, D.; Kaminski, M.; Cavalieri, D.; Dickinson, R.; Marquis, M.; Riggs, G.; Robinson, D.; VanWoert, M.; Wolfe, R.

2005-01-01

Snow and ice are the key components of the Earth's cryosphere, and their influence on the Earth's energy balance is very significant due at least in part to the large areal extent and high albedo characterizing these features. Large changes in the cryosphere have been measured over the last century and especially over the past decade, and remote sensing plays a pivotal role in documenting these changes. Many of NASA's Earth Observing System (EOS) products derived from instruments on the Terra, Aqua, and Ice, Cloud and land Elevation Satellite (ICESat) satellites are useful for measuring changes in features that are associated with climate change. The utility of the products is continually enhanced as the length of the time series increases. To gain a more coherent view of the cryosphere and its historical and recent changes, the EOS products may be employed together, in conjunction with other sources of data, and in models. To further this goal, the first EOS Snow and Ice Products Workshop was convened. The specific goals of the workshop were to provide current and prospective users of EOS snow and ice products up-to-date information on the products, their validation status and future enhancements, to help users utilize the data products through hands-on demonstrations, and to facilitate the integration of EOS products into models. Oral and poster sessions representing a wide variety of snow and ice topics were held; three panels were also convened to discuss workshop themes. Panel discussions focused on data fusion and assimilation of the products into models. Approximately 110 people attended, representing a wide array of interests and organizations in the cryospheric community.

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

NASA Astrophysics Data System (ADS)

Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.

2017-12-01

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

The Geolocation model for lunar-based Earth observation

NASA Astrophysics Data System (ADS)

Ding, Yixing; Liu, Guang; Ren, Yuanzhen; Ye, Hanlin; Guo, Huadong; Lv, Mingyang

2016-07-01

In recent years, people are more and more aware of that the earth need to treated as an entirety, and consequently to be observed in a holistic, systematic and multi-scale view. However, the interaction mechanism between the Earth's inner layers and outer layers is still unclear. Therefore, we propose to observe the Earth's inner layers and outer layers instantaneously on the Moon which may be helpful to the studies in climatology, meteorology, seismology, etc. At present, the Moon has been proved to be an irreplaceable platform for Earth's outer layers observation. Meanwhile, some discussions have been made in lunar-based observation of the Earth's inner layers, but the geolocation model of lunar-based observation has not been specified yet. In this paper, we present a geolocation model based on transformation matrix. The model includes six coordinate systems: The telescope coordinate system, the lunar local coordinate system, the lunar-reference coordinate system, the selenocentric inertial coordinate system, the geocentric inertial coordinate system and the geo-reference coordinate system. The parameters, lncluding the position of the Sun, the Earth, the Moon, the libration and the attitude of the Earth, can be acquired from the Ephemeris. By giving an elevation angle and an azimuth angle of the lunar-based telescope, this model links the image pixel to the ground point uniquely.

An adaptive tracking observer for failure-detection systems

NASA Technical Reports Server (NTRS)

Sidar, M.

1982-01-01

The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems.

PubMed

Favazza, Christopher P; Fetterly, Kenneth A; Hangiandreou, Nicholas J; Leng, Shuai; Schueler, Beth A

2015-01-01

Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks.

GEOS observation systems intercomparison investigation results

NASA Technical Reports Server (NTRS)

Berbert, J. H.

1974-01-01

The results of an investigation designed to determine the relative accuracy and precision of the different types of geodetic observation systems used by NASA is presented. A collocation technique was used to minimize the effects of uncertainties in the relative station locations and in the earth's gravity field model by installing accurate reference tracking systems close to the systems to be compared, and by precisely determining their relative survey. The Goddard laser and camera systems were shipped to selected sites, where they tracked the GEOS satellite simultaneously with other systems for an intercomparison observation.

Observing System Simulation Experiments for Fun and Profit

NASA Technical Reports Server (NTRS)

Prive, Nikki C.

2015-01-01

Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed

The Global Observing System in the Assimilation Context

NASA Technical Reports Server (NTRS)

Reinecker, Michele M.; Gelaro, R.; Pawson, S.; Reichle, R.; McCarty, W.

2011-01-01

Weather and climate analyses and predictions all rely on the global observing system. However, the observing system, whether atmosphere, ocean, or land surface, yields a diverse set of incomplete observations of the different components of Earth s environment. Data assimilation systems are essential to synthesize the wide diversity of in situ and remotely sensed observations into four-dimensional state estimates by combining the various observations with model-based estimates. Assimilation, or associated tools and products, are also useful in providing guidance for the evolution of the observing system of the future. This paper provides a brief overview of the global observing system and information gleaned through assimilation tools, and presents some evaluations of observing system gaps and issues.

Sensitivity Observing System Experiment (SOSE)-a new effective NWP-based tool in designing the global observing system

NASA Astrophysics Data System (ADS)

Marseille, Gert-Jan; Stoffelen, Ad; Barkmeijer, Jan

2008-03-01

Lacking an established methodology to test the potential impact of prospective extensions to the global observing system (GOS) in real atmospheric cases we developed such a method, called Sensitivity Observing System Experiment (SOSE). For example, since the GOS is non uniform it is of interest to investigate the benefit of complementary observing systems filling its gaps. In a SOSE adjoint sensitivity structures are used to define a pseudo true atmospheric state for the simulation of the prospective observing system. Next, the synthetic observations are used together with real observations from the existing GOS in a state-of-the-art Numerical Weather Prediction (NWP) model to assess the potential added value of the new observing system. Unlike full observing system simulation experiments (OSSE), SOSE can be applied to real extreme events that were badly forecast operationally and only requires the simulation of the new instrument. As such SOSE is an effective tool, for example, to define observation requirements for extensions to the GOS. These observation requirements may serve as input for the design of an operational network of prospective observing systems. In a companion paper we use SOSE to simulate potential future space borne Doppler Wind Lidar (DWL) scenarios and assess their capability to sample meteorologically sensitive areas not well captured by the current GOS, in particular over the Northern Hemisphere oceans.

Observation and integrated Earth-system science: A roadmap for 2016-2025

NASA Astrophysics Data System (ADS)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, Venkatachalam; Trenberth, Kevin; Asrar, Ghassem; Balmaseda, Magdalena; Burrows, John P.; Ciais, Philippe; Drinkwater, Mark; Friedlingstein, Pierre; Gobron, Nadine; Guilyardi, Eric; Halpern, David; Heimann, Martin; Johannessen, Johnny; Levelt, Pieternel F.; Lopez-Baeza, Ernesto; Penner, Joyce; Scholes, Robert; Shepherd, Ted

2016-05-01

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types of observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016-2025 and some of the issues to be faced. Observations that are organised on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the

Observer model optimization of a spectral mammography system

NASA Astrophysics Data System (ADS)

Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats

2010-04-01

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems

PubMed Central

Favazza, Christopher P.; Fetterly, Kenneth A.; Hangiandreou, Nicholas J.; Leng, Shuai; Schueler, Beth A.

2015-01-01

Abstract. Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks. PMID:26158086

Observations and a linear model of water level in an interconnected inlet-bay system

NASA Astrophysics Data System (ADS)

Aretxabaleta, Alfredo L.; Ganju, Neil K.; Butman, Bradford; Signell, Richard P.

2017-04-01

A system of barrier islands and back-barrier bays occurs along southern Long Island, New York, and in many coastal areas worldwide. Characterizing the bay physical response to water level fluctuations is needed to understand flooding during extreme events and evaluate their relation to geomorphological changes. Offshore sea level is one of the main drivers of water level fluctuations in semienclosed back-barrier bays. We analyzed observed water levels (October 2007 to November 2015) and developed analytical models to better understand bay water level along southern Long Island. An increase (˜0.02 m change in 0.17 m amplitude) in the dominant M2 tidal amplitude (containing the largest fraction of the variability) was observed in Great South Bay during mid-2014. The observed changes in both tidal amplitude and bay water level transfer from offshore were related to the dredging of nearby inlets and possibly the changing size of a breach across Fire Island caused by Hurricane Sandy (after December 2012). The bay response was independent of the magnitude of the fluctuations (e.g., storms) at a specific frequency. An analytical model that incorporates bay and inlet dimensions reproduced the observed transfer function in Great South Bay and surrounding areas. The model predicts the transfer function in Moriches and Shinnecock bays where long-term observations were not available. The model is a simplified tool to investigate changes in bay water level and enables the evaluation of future conditions and alternative geomorphological settings.

Observations and a linear model of water level in an interconnected inlet-bay system

USGS Publications Warehouse

Aretxabaleta, Alfredo; Ganju, Neil K.; Butman, Bradford; Signell, Richard

2017-01-01

A system of barrier islands and back-barrier bays occurs along southern Long Island, New York, and in many coastal areas worldwide. Characterizing the bay physical response to water level fluctuations is needed to understand flooding during extreme events and evaluate their relation to geomorphological changes. Offshore sea level is one of the main drivers of water level fluctuations in semienclosed back-barrier bays. We analyzed observed water levels (October 2007 to November 2015) and developed analytical models to better understand bay water level along southern Long Island. An increase (∼0.02 m change in 0.17 m amplitude) in the dominant M2 tidal amplitude (containing the largest fraction of the variability) was observed in Great South Bay during mid-2014. The observed changes in both tidal amplitude and bay water level transfer from offshore were related to the dredging of nearby inlets and possibly the changing size of a breach across Fire Island caused by Hurricane Sandy (after December 2012). The bay response was independent of the magnitude of the fluctuations (e.g., storms) at a specific frequency. An analytical model that incorporates bay and inlet dimensions reproduced the observed transfer function in Great South Bay and surrounding areas. The model predicts the transfer function in Moriches and Shinnecock bays where long-term observations were not available. The model is a simplified tool to investigate changes in bay water level and enables the evaluation of future conditions and alternative geomorphological settings.

The Role of Model and Initial Condition Error in Numerical Weather Forecasting Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2013-01-01

A series of experiments that explore the roles of model and initial condition error in numerical weather prediction are performed using an observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO). The use of an OSSE allows the analysis and forecast errors to be explicitly calculated, and different hypothetical observing networks can be tested with ease. In these experiments, both a full global OSSE framework and an 'identical twin' OSSE setup are utilized to compare the behavior of the data assimilation system and evolution of forecast skill with and without model error. The initial condition error is manipulated by varying the distribution and quality of the observing network and the magnitude of observation errors. The results show that model error has a strong impact on both the quality of the analysis field and the evolution of forecast skill, including both systematic and unsystematic model error components. With a realistic observing network, the analysis state retains a significant quantity of error due to systematic model error. If errors of the analysis state are minimized, model error acts to rapidly degrade forecast skill during the first 24-48 hours of forward integration. In the presence of model error, the impact of observation errors on forecast skill is small, but in the absence of model error, observation errors cause a substantial degradation of the skill of medium range forecasts.

NANOOS, the Northwest Association of Networked Ocean Observing Systems: a regional Integrated Ocean Observing System (IOOS) for the Pacific Northwest US

NASA Astrophysics Data System (ADS)

Newton, J.; Martin, D.; Kosro, M.

2012-12-01

NANOOS is the Northwest Association of Networked Ocean Observing Systems, the Pacific Northwest Regional Association of the United States Integrated Ocean Observing System (US IOOS). User driven since its inception in 2003, this regional observing system is responding to a variety of scientific and societal needs across its coastal ocean, estuaries, and shorelines. Regional priorities have been solicited and re-affirmed through active engagement with users and stakeholders. NANOOS membership is composed of an even mix of academic, governmental, industry, and non-profit organizations, who appoint representatives to the NANOOS Governing Council who confirm the priority applications of the observing system. NANOOS regional priorities are: Maritime Operations, Regional Fisheries, Ecosystem Assessment, Coastal Hazards, and Climate. NANOOS' regional coastal ocean observing system is implemented by seven partners (three universities, three state agencies, and one industry). Together, these partners conduct the observations, modeling, data management and communication, analysis products, education and outreach activities of NANOOS. Observations, designed to span coastal ocean, shorelines, and estuaries, include physical, chemical, biological and geological measurements. To date, modeling has been more limited in scope, but has provided the system with increased coverage for some parameters. The data management and communication system for NANOOS, led by the NANOOS Visualization System (NVS) is the cornerstone of the user interaction with NANOOS. NVS gives users access to observational data, both real time and archived, as well as modeling output. Given the diversity of user needs, measurements, and the complexity of the coastal environment, the challenge for the system is large. NANOOS' successes take advantage of technological advances, including real-time data transmission, profiling buoys, gliders, HF radars, and modeling. The most profound challenges NANOOS faces stem

Applications of Satellite Observations to Aerosol Analyses and Forecasting using the NAAPS Model and the DataFed Distributed Data System

NASA Astrophysics Data System (ADS)

Husar, R. B.; Hoijarvi, K.; Westphal, D. L.; Scheffe, R.; Keating, T.; Frank, N.; Poirot, R.; DuBois, D. W.; Bleiweiss, M. P.; Eberhard, W. L.; Menon, R.; Sethi, V.; Deshpande, A.

2012-12-01

Near-real-time (NRT) aerosol characterization, forecasting and decision support is now possible through the availability of (1) surface-based monitoring of regional PM concentrations, (2) global-scale columnar aerosol observations through satellites; (3) an aerosol model (NAAPS) that is capable of assimilating NRT satellite observations; and (4) an emerging cyber infrastructure for processing and distribution of data and model results (DataFed) for a wide range of users. This report describes the evolving NRT aerosol analysis and forecasting system and its applications at Federal and State and other AQ Agencies and groups. Through use cases and persistent real-world applications in the US and abroad, the report will show how satellite observations along with surface data and models are combined to aid decision support for AQ management, science and informing the public. NAAPS is the U.S. Navy's global aerosol and visibility forecast model that generates operational six-day global-scale forecasts for sulfate, dust, sea salt, and smoke aerosol. Through NAVDAS-AOD, NAAPS operationally assimilates filtered and corrected MODIS MOD04 aerosol optical depths and uses satellite-derived FLAMBÉ smoke emissions. Washington University's federated data system, DataFed, consist of a (1) data server which mediates the access to AQ datasets from distributed providers (NASA, NOAA, EPA, etc.,); (2) an AQ Data Catalog for finding and accessing data; and (3) a set of application programs/tools for browsing, exploring, comparing, aggregating, fusing data, evaluating models and delivering outputs through interactive visualization. NAAPS and DataFed are components of the Global Earth Observation System of Systems (GEOSS). Satellite data support the detection of long-range transported wind-blown dust and biomass smoke aerosols on hemispheric scales. The AQ management and analyst communities use the satellite/model data through DataFed and other channels as evidence for Exceptional Events

Research Opportunities from Emerging Atmospheric Observing and Modeling Capabilities.

NASA Astrophysics Data System (ADS)

Dabberdt, Walter F.; Schlatter, Thomas W.

1996-02-01

The Second Prospectus Development Team (PDT-2) of the U.S. Weather Research Program was charged with identifying research opportunities that are best matched to emerging operational and experimental measurement and modeling methods. The overarching recommendation of PDT-2 is that inputs for weather forecast models can best be obtained through the use of composite observing systems together with adaptive (or targeted) observing strategies employing both in situ and remote sensing. Optimal observing systems and strategies are best determined through a three-part process: observing system simulation experiments, pilot field measurement programs, and model-assisted data sensitivity experiments. Furthermore, the mesoscale research community needs easy and timely access to the new operational and research datasets in a form that can readily be reformatted into existing software packages for analysis and display. The value of these data is diminished to the extent that they remain inaccessible.The composite observing system of the future must combine synoptic observations, routine mobile observations, and targeted observations, as the current or forecast situation dictates. High costs demand fuller exploitation of commercial aircraft, meteorological and navigation [Global Positioning System (GPS)] satellites, and Doppler radar. Single observing systems must be assessed in the context of a composite system that provides complementary information. Maintenance of the current North American rawinsonde network is critical for progress in both research-oriented and operational weather forecasting.Adaptive sampling strategies are designed to improve large-scale and regional weather prediction but they will also improve diagnosis and prediction of flash flooding, air pollution, forest fire management, and other environmental emergencies. Adaptive measurements can be made by piloted or unpiloted aircraft. Rawinsondes can be launched and satellites can be programmed to make

Observation and integrated Earth-system science: A roadmap for 2016–2025

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, V.

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types ofmore » observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016–2025 and some of the issues to be faced. Observations that are organized on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the

Technical report series on global modeling and data assimilation. Volume 4: Documentation of the Goddard Earth Observing System (GEOS) data assimilation system, version 1

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Pfaendtner, James; Bloom, Stephen; Lamich, David; Seablom, Michael; Sienkiewicz, Meta; Stobie, James; Dasilva, Arlindo

1995-01-01

This report describes the analysis component of the Goddard Earth Observing System, Data Assimilation System, Version 1 (GEOS-1 DAS). The general features of the data assimilation system are outlined, followed by a thorough description of the statistical interpolation algorithm, including specification of error covariances and quality control of observations. We conclude with a discussion of the current status of development of the GEOS data assimilation system. The main components of GEOS-1 DAS are an atmospheric general circulation model and an Optimal Interpolation algorithm. The system is cycled using the Incremental Analysis Update (IAU) technique in which analysis increments are introduced as time independent forcing terms in a forecast model integration. The system is capable of producing dynamically balanced states without the explicit use of initialization, as well as a time-continuous representation of non- observables such as precipitation and radiational fluxes. This version of the data assimilation system was used in the five-year reanalysis project completed in April 1994 by Goddard's Data Assimilation Office (DAO) Data from this reanalysis are available from the Goddard Distributed Active Center (DAAC), which is part of NASA's Earth Observing System Data and Information System (EOSDIS). For information on how to obtain these data sets, contact the Goddard DAAC at (301) 286-3209, EMAIL daac@gsfc.nasa.gov.

A simple parametric model observer for quality assurance in computer tomography

NASA Astrophysics Data System (ADS)

Anton, M.; Khanin, A.; Kretz, T.; Reginatto, M.; Elster, C.

2018-04-01

Model observers are mathematical classifiers that are used for the quality assessment of imaging systems such as computer tomography. The quality of the imaging system is quantified by means of the performance of a selected model observer. For binary classification tasks, the performance of the model observer is defined by the area under its ROC curve (AUC). Typically, the AUC is estimated by applying the model observer to a large set of training and test data. However, the recording of these large data sets is not always practical for routine quality assurance. In this paper we propose as an alternative a parametric model observer that is based on a simple phantom, and we provide a Bayesian estimation of its AUC. It is shown that a limited number of repeatedly recorded images (10–15) is already sufficient to obtain results suitable for the quality assessment of an imaging system. A MATLAB® function is provided for the calculation of the results. The performance of the proposed model observer is compared to that of the established channelized Hotelling observer and the nonprewhitening matched filter for simulated images as well as for images obtained from a low-contrast phantom on an x-ray tomography scanner. The results suggest that the proposed parametric model observer, along with its Bayesian treatment, can provide an efficient, practical alternative for the quality assessment of CT imaging systems.

Weather Observation Systems and Efficiency of Fighting Forest Fires

NASA Astrophysics Data System (ADS)

Khabarov, N.; Moltchanova, E.; Obersteiner, M.

2007-12-01

Weather observation is an essential component of modern forest fire management systems. Satellite and in-situ based weather observation systems might help to reduce forest loss, human casualties and destruction of economic capital. In this paper, we develop and apply a methodology to assess the benefits of various weather observation systems on reductions of burned area due to early fire detection. In particular, we consider a model where the air patrolling schedule is determined by a fire hazard index. The index is computed from gridded daily weather data for the area covering parts Spain and Portugal. We conduct a number of simulation experiments. First, the resolution of the original data set is artificially reduced. The reduction of the total forest burned area associated with air patrolling based on a finer weather grid indicates the benefit of using higher spatially resolved weather observations. Second, we consider a stochastic model to simulate forest fires and explore the sensitivity of the model with respect to the quality of input data. The analysis of combination of satellite and ground monitoring reveals potential cost saving due to a "system of systems effect" and substantial reduction in burned area. Finally, we estimate the marginal improvement schedule for loss of life and economic capital as a function of the improved fire observing system.

Deployment and Evaluation of an Observations Data Model

NASA Astrophysics Data System (ADS)

Horsburgh, J. S.; Tarboton, D. G.; Zaslavsky, I.; Maidment, D. R.; Valentine, D.

2007-12-01

Environmental observations are fundamental to hydrology and water resources, and the way these data are organized and manipulated either enables or inhibits the analyses that can be performed. The CUAHSI Hydrologic Information System project is developing information technology infrastructure to support hydrologic science. This includes an Observations Data Model (ODM) that provides a new and consistent format for the storage and retrieval of environmental observations in a relational database designed to facilitate integrated analysis of large datasets collected by multiple investigators. Within this data model, observations are stored with sufficient ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used, and to provide traceable heritage from raw measurements to useable information. The design is based upon a relational database model that exposes each single observation as a record, taking advantage of the capability in relational database systems for querying based upon data values and enabling cross dimension data retrieval and analysis. This data model has been deployed, as part of the HIS Server, at the WATERS Network test bed observatories across the U.S where it serves as a repository for real time data in the observatory information system. The ODM holds the data that is then made available to investigators and the public through web services and the Data Access System for Hydrology (DASH) map based interface. In the WATERS Network test bed settings the ODM has been used to ingest, analyze and publish data from a variety of sources and disciplines. This paper will present an evaluation of the effectiveness of this initial deployment and the revisions that are being instituted to address shortcomings. The ODM represents a new, systematic way for hydrologists, scientists, and engineers to organize and share their data and thereby facilitate a fuller integrated understanding of water resources based on

A Community Data Model for Hydrologic Observations

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Horsburgh, J. S.; Zaslavsky, I.; Maidment, D. R.; Valentine, D.; Jennings, B.

2006-12-01

The CUAHSI Hydrologic Information System project is developing information technology infrastructure to support hydrologic science. Hydrologic information science involves the description of hydrologic environments in a consistent way, using data models for information integration. This includes a hydrologic observations data model for the storage and retrieval of hydrologic observations in a relational database designed to facilitate data retrieval for integrated analysis of information collected by multiple investigators. It is intended to provide a standard format to facilitate the effective sharing of information between investigators and to facilitate analysis of information within a single study area or hydrologic observatory, or across hydrologic observatories and regions. The observations data model is designed to store hydrologic observations and sufficient ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used and provide traceable heritage from raw measurements to usable information. The design is based on the premise that a relational database at the single observation level is most effective for providing querying capability and cross dimension data retrieval and analysis. This premise is being tested through the implementation of a prototype hydrologic observations database, and the development of web services for the retrieval of data from and ingestion of data into the database. These web services hosted by the San Diego Supercomputer center make data in the database accessible both through a Hydrologic Data Access System portal and directly from applications software such as Excel, Matlab and ArcGIS that have Standard Object Access Protocol (SOAP) capability. This paper will (1) describe the data model; (2) demonstrate the capability for representing diverse data in the same database; (3) demonstrate the use of the database from applications software for the performance of hydrologic analysis

Characteristics of Operational Space Weather Forecasting: Observations and Models

NASA Astrophysics Data System (ADS)

Berger, Thomas; Viereck, Rodney; Singer, Howard; Onsager, Terry; Biesecker, Doug; Rutledge, Robert; Hill, Steven; Akmaev, Rashid; Milward, George; Fuller-Rowell, Tim

2015-04-01

In contrast to research observations, models and ground support systems, operational systems are characterized by real-time data streams and run schedules, with redundant backup systems for most elements of the system. We review the characteristics of operational space weather forecasting, concentrating on the key aspects of ground- and space-based observations that feed models of the coupled Sun-Earth system at the NOAA/Space Weather Prediction Center (SWPC). Building on the infrastructure of the National Weather Service, SWPC is working toward a fully operational system based on the GOES weather satellite system (constant real-time operation with back-up satellites), the newly launched DSCOVR satellite at L1 (constant real-time data network with AFSCN backup), and operational models of the heliosphere, magnetosphere, and ionosphere/thermosphere/mesophere systems run on the Weather and Climate Operational Super-computing System (WCOSS), one of the worlds largest and fastest operational computer systems that will be upgraded to a dual 2.5 Pflop system in 2016. We review plans for further operational space weather observing platforms being developed in the context of the Space Weather Operations Research and Mitigation (SWORM) task force in the Office of Science and Technology Policy (OSTP) at the White House. We also review the current operational model developments at SWPC, concentrating on the differences between the research codes and the modified real-time versions that must run with zero fault tolerance on the WCOSS systems. Understanding the characteristics and needs of the operational forecasting community is key to producing research into the coupled Sun-Earth system with maximal societal benefit.

An Observation-based Assessment of Instrument Requirements for a Future Precipitation Process Observing System

NASA Astrophysics Data System (ADS)

Nelson, E.; L'Ecuyer, T. S.; Wood, N.; Smalley, M.; Kulie, M.; Hahn, W.

2017-12-01

Global models exhibit substantial biases in the frequency, intensity, duration, and spatial scales of precipitation systems. Much of this uncertainty stems from an inadequate representation of the processes by which water is cycled between the surface and atmosphere and, in particular, those that govern the formation and maintenance of cloud systems and their propensity to form the precipitation. Progress toward improving precipitation process models requires observing systems capable of quantifying the coupling between the ice content, vertical mass fluxes, and precipitation yield of precipitating cloud systems. Spaceborne multi-frequency, Doppler radar offers a unique opportunity to address this need but the effectiveness of such a mission is heavily dependent on its ability to actually observe the processes of interest in the widest possible range of systems. Planning for a next generation precipitation process observing system should, therefore, start with a fundamental evaluation of the trade-offs between sensitivity, resolution, sampling, cost, and the overall potential scientific yield of the mission. Here we provide an initial assessment of the scientific and economic trade-space by evaluating hypothetical spaceborne multi-frequency radars using a combination of current real-world and model-derived synthetic observations. Specifically, we alter the field of view, vertical resolution, and sensitivity of a hypothetical Ka- and W-band radar system and propagate those changes through precipitation detection and intensity retrievals. The results suggest that sampling biases introduced by reducing sensitivity disproportionately affect the light rainfall and frozen precipitation regimes that are critical for warm cloud feedbacks and ice sheet mass balance, respectively. Coarser spatial resolution observations introduce regime-dependent biases in both precipitation occurrence and intensity that depend on cloud regime, with even the sign of the bias varying within a

Finding the Needles in the Haystacks: High-Fidelity Models of the Modern and Archean Solar System for Simulating Exoplanet Observations

NASA Technical Reports Server (NTRS)

Roberge, Aki; Rizzo, Maxime J.; Lincowski, Andrew P.; Arney, Giada N.; Stark, Christopher C.; Robinson, Tyler D.; Snyder, Gregory F.; Pueyo, Laurent; Zimmerman, Neil T.; Jansen, Tiffany;

The Trojan-Hilda-KBO connection: An observational test of solar system evolution models

NASA Astrophysics Data System (ADS)

Wong, Ian; Brown, Michael

2017-10-01

Over the past few decades, many theories have been devised to explain the observed solar system architecture. The current paradigm posits that a significant reorganization of the outer Solar System occurred after the end of planet formation. Specifically, it is hypothesized that Jupiter and Saturn crossed a mutual mean motion resonance, leading to a chaotic expansion of the ice giants’ orbits that disrupted the large population of planetesimals situated further out. While the majority of these bodies were ejected from the Solar System, a fraction of them were retained as the present-day Kuiper Belt, while others were scattered inward and captured into resonances with Jupiter to become the Trojans and Hildas. Dynamical instability models invariably predict that Trojans, Hildas, and Kuiper Belt objects (KBOs) were sourced from the same primordial body of outer solar system planetesimals. Therefore, comparison of these minor body populations serves as one of the few available observational tests of our present understanding of solar system evolution.We present the results of a series of studies aimed at synthesizing a detailed picture of Trojans and related asteroid populations. By combining analyses of archival data with new photometric surveys, we have derived the first debiased color distributions of Trojans and KBOs and extended/refined our knowledge of their respective size distributions. In addition, we have explored the peculiar color bimodality attested in the Trojans, Hildas, and KBOs, which indicates the presence of two sub-populations. As part of our continuing efforts to characterize the surface composition of these bodies, we have also obtained new near-infrared spectra of Hildas for comparison with previously published spectra of Trojans covering the same wavelength region. We have utilized the full body of observations to formulate hypotheses regarding the formation, composition, and dynamical/chemical evolution of the primordial outer solar system

The Trojan-Hilda-KBO connection: An observational test of solar system evolution models

NASA Astrophysics Data System (ADS)

Wong, I.; Brown, M. E.

2017-12-01

Over the past few decades, many theories have been devised to explain the observed solar system architecture. The current paradigm posits that a significant reorganization of the outer Solar System occurred after the end of planet formation. Specifically, it is hypothesized that Jupiter and Saturn crossed a mutual mean motion resonance, leading to a chaotic expansion of the ice giants' orbits that disrupted the large population of planetesimals situated further out. While the majority of these bodies were ejected from the Solar System, a fraction of them were retained as the present-day Kuiper Belt, while others were scattered inward and captured into resonances with Jupiter to become the Trojans and Hildas. Dynamical instability models invariably predict that Trojans, Hildas, and Kuiper Belt objects (KBOs) were sourced from the same primordial body of outer solar system planetesimals. Therefore, comparison of these minor body populations serves as one of the few available observational tests of our present understanding of solar system evolution. We present the results of a series of studies aimed at synthesizing a detailed picture of Trojans and related asteroid populations. By combining analyses of archival data with new photometric surveys, we have derived the first debiased color distributions of Trojans and KBOs and extended/refined our knowledge of their respective size distributions. In addition, we have explored the peculiar color bimodality attested in the Trojans, Hildas, and KBOs, which indicates the presence of two sub-populations. As part of our continuing efforts to characterize the surface composition of these bodies, we have also obtained new near-infrared spectra of Hildas for comparison with previously published spectra of Trojans covering the same wavelength region. We have utilized the full body of observations to formulate hypotheses regarding the formation, composition, and dynamical/chemical evolution of the primordial outer solar system

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth

PubMed Central

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth.

PubMed

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern

An Introduction to Observing System Simulation Experiments

NASA Technical Reports Server (NTRS)

Prive, Nikki C.

2017-01-01

Observing System Simulation Experiments (OSSEs) are used to estimate the potential impact of proposed new instruments and data on numerical weather prediction. OSSEs can also be used to help design new observing platforms and to investigate the behavior of data assimilation systems. A basic overview of how to design and perform an OSSE will be given, as well as best practices and pitfalls. Some examples using the OSSE framework developed at the NASA Global Modeling and Assimilation Office will be shown.

Demonstrating the Alaska Ocean Observing System in Prince William Sound

NASA Astrophysics Data System (ADS)

Schoch, G. Carl; McCammon, Molly

2013-07-01

The Alaska Ocean Observing System and the Oil Spill Recovery Institute developed a demonstration project over a 5 year period in Prince William Sound. The primary goal was to develop a quasi-operational system that delivers weather and ocean information in near real time to diverse user communities. This observing system now consists of atmospheric and oceanic sensors, and a new generation of computer models to numerically simulate and forecast weather, waves, and ocean circulation. A state of the art data management system provides access to these products from one internet portal at http://www.aoos.org. The project culminated in a 2009 field experiment that evaluated the observing system and performance of the model forecasts. Observations from terrestrial weather stations and weather buoys validated atmospheric circulation forecasts. Observations from wave gages on weather buoys validated forecasts of significant wave heights and periods. There was an emphasis on validation of surface currents forecasted by the ocean circulation model for oil spill response and search and rescue applications. During the 18 day field experiment a radar array mapped surface currents and drifting buoys were deployed. Hydrographic profiles at fixed stations, and by autonomous vehicles along transects, were made to acquire measurements through the water column. Terrestrial weather stations were the most reliable and least costly to operate, and in situ ocean sensors were more costly and considerably less reliable. The radar surface current mappers were the least reliable and most costly but provided the assimilation and validation data that most improved ocean circulation forecasts. We describe the setting of Prince William Sound and the various observational platforms and forecast models of the observing system, and discuss recommendations for future development.

Made-to-measure modelling of observed galaxy dynamics

NASA Astrophysics Data System (ADS)

Bovy, Jo; Kawata, Daisuke; Hunt, Jason A. S.

2018-01-01

Amongst dynamical modelling techniques, the made-to-measure (M2M) method for modelling steady-state systems is amongst the most flexible, allowing non-parametric distribution functions in complex gravitational potentials to be modelled efficiently using N-body particles. Here, we propose and test various improvements to the standard M2M method for modelling observed data, illustrated using the simple set-up of a one-dimensional harmonic oscillator. We demonstrate that nuisance parameters describing the modelled system's orientation with respect to the observer - e.g. an external galaxy's inclination or the Sun's position in the Milky Way - as well as the parameters of an external gravitational field can be optimized simultaneously with the particle weights. We develop a method for sampling from the high-dimensional uncertainty distribution of the particle weights. We combine this in a Gibbs sampler with samplers for the nuisance and potential parameters to explore the uncertainty distribution of the full set of parameters. We illustrate our M2M improvements by modelling the vertical density and kinematics of F-type stars in Gaia DR1. The novel M2M method proposed here allows full probabilistic modelling of steady-state dynamical systems, allowing uncertainties on the non-parametric distribution function and on nuisance parameters to be taken into account when constraining the dark and baryonic masses of stellar systems.

Examination of Observation Impacts derived from OSEs and Adjoint Models

NASA Technical Reports Server (NTRS)

Gelaro, Ronald

2008-01-01

With the adjoint of a data assimilation system, the impact of any or all assimilated observations on measures of forecast skill can be estimated accurately and efficiently. The approach allows aggregation of results in terms of individual data types, channels or locations, all computed simultaneously. In this study, adjoint-based estimates of observation impact are compared with results from standard observing system experiments (OSEs) in the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) GEOS-5 system. The two approaches are shown to provide unique, but complimentary, information. Used together, they reveal both redundancies and dependencies between observing system impacts as observations are added or removed. Understanding these dependencies poses a major challenge for optimizing the use of the current observational network and defining requirements for future observing systems.

Status of the NASA GMAO Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2014-01-01

An Observing System Simulation Experiment (OSSE) is a pure modeling study used when actual observations are too expensive or difficult to obtain. OSSEs are valuable tools for determining the potential impact of new observing systems on numerical weather forecasts and for evaluation of data assimilation systems (DAS). An OSSE has been developed at the NASA Global Modeling and Assimilation Office (GMAO, Errico et al 2013). The GMAO OSSE uses a 13-month integration of the European Centre for Medium- Range Weather Forecasts 2005 operational model at T511/L91 resolution for the Nature Run (NR). Synthetic observations have been updated so that they are based on real observations during the summer of 2013. The emulated observation types include AMSU-A, MHS, IASI, AIRS, and HIRS4 radiance data, GPS-RO, and conventional types including aircraft, rawinsonde, profiler, surface, and satellite winds. The synthetic satellite wind observations are colocated with the NR cloud fields, and the rawinsondes are advected during ascent using the NR wind fields. Data counts for the synthetic observations are matched as closely as possible to real data counts, as shown in Figure 2. Errors are added to the synthetic observations to emulate representativeness and instrument errors. The synthetic errors are calibrated so that the statistics of observation innovation and analysis increments in the OSSE are similar to the same statistics for assimilation of real observations, in an iterative method described by Errico et al (2013). The standard deviations of observation minus forecast (xo-H(xb)) are compared for the OSSE and real data in Figure 3. The synthetic errors include both random, uncorrelated errors, and an additional correlated error component for some observational types. Vertically correlated errors are included for conventional sounding data and GPS-RO, and channel correlated errors are introduced to AIRS and IASI (Figure 4). HIRS, AMSU-A, and MHS have a component of horizontally

Modeling observations of solar coronal mass ejections with heliospheric imagers verified with the Heliophysics System Observatory.

PubMed

Möstl, C; Isavnin, A; Boakes, P D; Kilpua, E K J; Davies, J A; Harrison, R A; Barnes, D; Krupar, V; Eastwood, J P; Good, S W; Forsyth, R J; Bothmer, V; Reiss, M A; Amerstorfer, T; Winslow, R M; Anderson, B J; Philpott, L C; Rodriguez, L; Rouillard, A P; Gallagher, P; Nieves-Chinchilla, T; Zhang, T L

2017-07-01

We present an advance toward accurately predicting the arrivals of coronal mass ejections (CMEs) at the terrestrial planets, including Earth. For the first time, we are able to assess a CME prediction model using data over two thirds of a solar cycle of observations with the Heliophysics System Observatory. We validate modeling results of 1337 CMEs observed with the Solar Terrestrial Relations Observatory (STEREO) heliospheric imagers (HI) (science data) from 8 years of observations by five in situ observing spacecraft. We use the self-similar expansion model for CME fronts assuming 60° longitudinal width, constant speed, and constant propagation direction. With these assumptions we find that 23%-35% of all CMEs that were predicted to hit a certain spacecraft lead to clear in situ signatures, so that for one correct prediction, two to three false alarms would have been issued. In addition, we find that the prediction accuracy does not degrade with the HI longitudinal separation from Earth. Predicted arrival times are on average within 2.6 ± 16.6 h difference of the in situ arrival time, similar to analytical and numerical modeling, and a true skill statistic of 0.21. We also discuss various factors that may improve the accuracy of space weather forecasting using wide-angle heliospheric imager observations. These results form a first-order approximated baseline of the prediction accuracy that is possible with HI and other methods used for data by an operational space weather mission at the Sun-Earth L5 point.

Modeling observations of solar coronal mass ejections with heliospheric imagers verified with the Heliophysics System Observatory

PubMed Central

Isavnin, A.; Boakes, P. D.; Kilpua, E. K. J.; Davies, J. A.; Harrison, R. A.; Barnes, D.; Krupar, V.; Eastwood, J. P.; Good, S. W.; Forsyth, R. J.; Bothmer, V.; Reiss, M. A.; Amerstorfer, T.; Winslow, R. M.; Anderson, B. J.; Philpott, L. C.; Rodriguez, L.; Rouillard, A. P.; Gallagher, P.; Nieves‐Chinchilla, T.; Zhang, T. L.

2017-01-01

Abstract We present an advance toward accurately predicting the arrivals of coronal mass ejections (CMEs) at the terrestrial planets, including Earth. For the first time, we are able to assess a CME prediction model using data over two thirds of a solar cycle of observations with the Heliophysics System Observatory. We validate modeling results of 1337 CMEs observed with the Solar Terrestrial Relations Observatory (STEREO) heliospheric imagers (HI) (science data) from 8 years of observations by five in situ observing spacecraft. We use the self‐similar expansion model for CME fronts assuming 60° longitudinal width, constant speed, and constant propagation direction. With these assumptions we find that 23%–35% of all CMEs that were predicted to hit a certain spacecraft lead to clear in situ signatures, so that for one correct prediction, two to three false alarms would have been issued. In addition, we find that the prediction accuracy does not degrade with the HI longitudinal separation from Earth. Predicted arrival times are on average within 2.6 ± 16.6 h difference of the in situ arrival time, similar to analytical and numerical modeling, and a true skill statistic of 0.21. We also discuss various factors that may improve the accuracy of space weather forecasting using wide‐angle heliospheric imager observations. These results form a first‐order approximated baseline of the prediction accuracy that is possible with HI and other methods used for data by an operational space weather mission at the Sun‐Earth L5 point. PMID:28983209

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data

NASA Astrophysics Data System (ADS)

Song, Xia; Hoffman, Forrest M.; Iversen, Colleen M.; Yin, Yunhe; Kumar, Jitendra; Ma, Chun; Xu, Xiaofeng

2017-09-01

Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. We compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root (r = 0.71) and total vegetation (r = 0.62). However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S-10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1-0.8). There were substantial inconsistencies between ESM-derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.

Integrated Arctic Observation System Development Under Horizon 2020

NASA Astrophysics Data System (ADS)

Sandven, S.

2016-12-01

The overall objective of INTAROS is to develop an integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. INTAROS will have a strong multidisciplinary focus, with tools for integration of data from atmosphere, ocean, cryosphere and terrestrial sciences, provided by institutions in Europe, North America and Asia. Satellite earth observation data plays an increasingly important role in such observing systems, because the amount of EO data for observing the global climate and environment grows year by year. In situ observing systems are much more limited due to logistical constraints and cost limitations. The sparseness of in situ data is therefore the largest gap in the overall observing system. INTAROS will assess strengths and weaknesses of existing observing systems and contribute with innovative solutions to fill some of the critical gaps in the in situ observing network. INTAROS will develop a platform, iAOS, to search for and access data from distributed databases. The evolution into a sustainable Arctic observing system requires coordination, mobilization and cooperation between the existing European and international infrastructures (in-situ and remote including space-based), the modeling communities and relevant stakeholder groups. INTAROS will include development of community-based observing systems, where local knowledge is merged with scientific data. An integrated Arctic Observation System will enable better-informed decisions and better-documented processes within key sectors (e.g. local communities, shipping, tourism, fishing), in order to strengthen the societal and economic role of the Arctic region and support the EU strategy for the Arctic and related maritime and environmental policies.

Advancing an Information Model for Environmental Observations

NASA Astrophysics Data System (ADS)

Horsburgh, J. S.; Aufdenkampe, A. K.; Hooper, R. P.; Lehnert, K. A.; Schreuders, K.; Tarboton, D. G.; Valentine, D. W.; Zaslavsky, I.

2011-12-01

Observational data are fundamental to hydrology and water resources, and the way they are organized, described, and shared either enables or inhibits the analyses that can be performed using the data. The CUAHSI Hydrologic Information System (HIS) project is developing cyberinfrastructure to support hydrologic science by enabling better access to hydrologic data. HIS is composed of three major components. HydroServer is a software stack for publishing time series of hydrologic observations on the Internet as well as geospatial data using standards-based web feature, map, and coverage services. HydroCatalog is a centralized facility that catalogs the data contents of individual HydroServers and enables search across them. HydroDesktop is a client application that interacts with both HydroServer and HydroCatalog to discover, download, visualize, and analyze hydrologic observations published on one or more HydroServers. All three components of HIS are founded upon an information model for hydrologic observations at stationary points that specifies the entities, relationships, constraints, rules, and semantics of the observational data and that supports its data services. Within this information model, observations are described with ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used, and to provide traceable heritage from raw measurements to useable information. Physical implementations of this information model include the Observations Data Model (ODM) for storing hydrologic observations, Water Markup Language (WaterML) for encoding observations for transmittal over the Internet, the HydroCatalog metadata catalog database, and the HydroDesktop data cache database. The CUAHSI HIS and this information model have now been in use for several years, and have been deployed across many different academic institutions as well as across several national agency data repositories. Additionally, components of the HIS

The diversity of planetary system architectures: contrasting theory with observations

NASA Astrophysics Data System (ADS)

Miguel, Y.; Guilera, O. M.; Brunini, A.

2011-10-01

In order to explain the observed diversity of planetary system architectures and relate this primordial diversity to the initial properties of the discs where they were born, we develop a semi-analytical model for computing planetary system formation. The model is based on the core instability model for the gas accretion of the embryos and the oligarchic growth regime for the accretion of the solid cores. Two regimes of planetary migration are also included. With this model, we consider different initial conditions based on recent results of protoplanetary disc observations to generate a variety of planetary systems. These systems are analysed statistically, exploring the importance of several factors that define the planetary system birth environment. We explore the relevance of the mass and size of the disc, metallicity, mass of the central star and time-scale of gaseous disc dissipation in defining the architecture of the planetary system. We also test different values of some key parameters of our model to find out which factors best reproduce the diverse sample of observed planetary systems. We assume different migration rates and initial disc profiles, in the context of a surface density profile motivated by similarity solutions. According to this, and based on recent protoplanetary disc observational data, we predict which systems are the most common in the solar neighbourhood. We intend to unveil whether our Solar system is a rarity or whether more planetary systems like our own are expected to be found in the near future. We also analyse which is the more favourable environment for the formation of habitable planets. Our results show that planetary systems with only terrestrial planets are the most common, being the only planetary systems formed when considering low-metallicity discs, which also represent the best environment for the development of rocky, potentially habitable planets. We also found that planetary systems like our own are not rare in the

A perspective on sustained marine observations for climate modelling and prediction

PubMed Central

Dunstone, Nick J.

2014-01-01

Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow

A perspective on sustained marine observations for climate modelling and prediction.

PubMed

Dunstone, Nick J

2014-09-28

Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow

NOAA Observing System Integrated Analysis (NOSIA): development and support to the NOAA Satellite Observing System Architecture

NASA Astrophysics Data System (ADS)

Reining, R. C.; Cantrell, L. E., Jr.; Helms, D.; LaJoie, M.; Pratt, A. S.; Ries, V.; Taylor, J.; Yuen-Murphy, M. A.

2016-12-01

There is a deep relationship between NOSIA-II and the Federal Earth Observation Assessment (EOA) efforts (EOA 2012 and 2016) chartered under the National Science and Technology Council, Committee on Environment, Natural Resources, and Sustainability, co-chaired by the White House Office of Science and Technology Policy, NASA, NOAA, and USGS. NOSIA-1, which was conducted with a limited scope internal to NOAA in 2010, developed the methodology and toolset that was adopted for EOA 2012, and NOAA staffed the team that conducted the data collection, modeling, and analysis effort for EOA 2012. EOA 2012 was the first-ever integrated analysis of the relative impact of 379 observing systems and data sources contributing to the key objectives identified for 13 Societal Benefit Areas (SBA) including Weather, Climate, Disasters, Oceans and Coastal Resources, and Water Resources. This effort culminated in the first National Plan for Civil Earth Observations. NOAA conducted NOSIA-II starting in 2012 to extend the NOSIA methodology across all of NOAA's Mission Service Areas, covering a representative sample (over 1000) of NOAA's products and services. The detailed information from NOSIA-II is being integrated into EOA 2016 to underpin a broad array of Key Products, Services, and (science) Objectives (KPSO) identified by the inter-agency SBA teams. EOA 2016 is expected to provide substantially greater insight into the cross-agency impacts of observing systems contributing to a wide array of KPSOs, and by extension, to societal benefits flowing from these public-facing products. NOSIA-II is being adopted by NOAA as a corporate decision-analysis and support capability to inform leadership decisions on its integrated observing systems portfolio. Application examples include assessing the agency-wide impacts of planned decommissioning of ships and aircraft in NOAA's fleet, and the relative cost-effectiveness of alternative space-based architectures in the post-GOES-R and JPSS era

Observations and Modeling of Merging Galaxy Clusters

NASA Astrophysics Data System (ADS)

Golovich, Nathan Ryan

Context: Galaxy clusters grow hierarchically with continuous accretion bookended by major merging events that release immense gravitational potential energy (as much as ˜1065 erg). This energy creates an environment for rich astrophysics. Precise measurements of the dark matter halo, intracluster medium, and galaxy population have resulted in a number of important results including dark matter constraints and explanations of the generation of cosmic rays. However, since the timescale of major mergers (˜several Gyr) relegates observations of individual systems to mere snapshots, these results are difficult to understand under a consistent dynamical framework. While computationally expensive simulations are vital in this regard, the vastness of parameter space has necessitated simulations of idealized mergers that are unlikely to capture the full richness. Merger speeds, geometries, and timescales each have a profound consequential effect, but even these simple dynamical properties of the mergers are often poorly understood. A method to identify and constrain the best systems for probing the rich astrophysics of merging clusters is needed. Such a method could then be utilized to prioritize observational follow up and best inform proper exploration of dynamical phase space. Task: In order to identify and model a large number of systems, in this dissertation, we compile an ensemble of major mergers each containing radio relics. We then complete a pan-chromatic study of these 29 systems including wide field optical photometry, targeted optical spectroscopy of member galaxies, radio, and X-ray observations. We use the optical observations to model the galaxy substructure and estimate line of sight motion. In conjunction with the radio and X-ray data, these substructure models helped elucidate the most likely merger scenario for each system and further constrain the dynamical properties of each system. We demonstrate the power of this technique through detailed analyses

Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model

NASA Technical Reports Server (NTRS)

Putnam, Williama

2011-01-01

The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.

Nonlinear Inference in Partially Observed Physical Systems and Deep Neural Networks

NASA Astrophysics Data System (ADS)

Rozdeba, Paul J.

The problem of model state and parameter estimation is a significant challenge in nonlinear systems. Due to practical considerations of experimental design, it is often the case that physical systems are partially observed, meaning that data is only available for a subset of the degrees of freedom required to fully model the observed system's behaviors and, ultimately, predict future observations. Estimation in this context is highly complicated by the presence of chaos, stochasticity, and measurement noise in dynamical systems. One of the aims of this dissertation is to simultaneously analyze state and parameter estimation in as a regularized inverse problem, where the introduction of a model makes it possible to reverse the forward problem of partial, noisy observation; and as a statistical inference problem using data assimilation to transfer information from measurements to the model states and parameters. Ultimately these two formulations achieve the same goal. Similar aspects that appear in both are highlighted as a means for better understanding the structure of the nonlinear inference problem. An alternative approach to data assimilation that uses model reduction is then examined as a way to eliminate unresolved nonlinear gating variables from neuron models. In this formulation, only measured variables enter into the model, and the resulting errors are themselves modeled by nonlinear stochastic processes with memory. Finally, variational annealing, a data assimilation method previously applied to dynamical systems, is introduced as a potentially useful tool for understanding deep neural network training in machine learning by exploiting similarities between the two problems.

Life Cycle of Tropical Convection and Anvil in Observations and Models

NASA Astrophysics Data System (ADS)

McFarlane, S. A.; Hagos, S. M.; Comstock, J. M.

2011-12-01

Tropical convective clouds are important elements of the hydrological cycle and produce extensive cirrus anvils that strongly affect the tropical radiative energy balance. To improve simulations of the global water and energy cycles and accurately predict both precipitation and cloud radiative feedbacks, models need to realistically simulate the lifecycle of tropical convection, including the formation and radiative properties of ice anvil clouds. By combining remote sensing datasets from precipitation and cloud radars at the Atmospheric Radiation Measurement (ARM) Darwin site with geostationary satellite data, we can develop observational understanding of the lifetime of convective systems and the links between the properties of convective systems and their associated anvil clouds. The relationships between convection and anvil in model simulations can then be compared to those seen in the observations to identify areas for improvement in the model simulations. We identify and track tropical convective systems in the Tropical Western Pacific using geostationary satellite observations. We present statistics of the tropical convective systems including size, age, and intensity and classify the lifecycle stage of each system as developing, mature, or dissipating. For systems that cross over the ARM Darwin site, information on convective intensity and anvil properties are obtained from the C-Pol precipitation radar and MMCR cloud radar, respectively, and are examined as a function of the system lifecycle. Initial results from applying the convective identification and tracking algorithm to a tropical simulation from the Weather Research and Forecasting (WRF) model run show that the model produces reasonable overall statistics of convective systems, but details of the life cycle (such as diurnal cycle, system tracks) differ from the observations. Further work will focus on the role of atmospheric temperature and moisture profiles in the model's convective life cycle.

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

NASA Technical Reports Server (NTRS)

Larson, Jay W.

1998-01-01

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

A Study of the Carbon Cycle Using NASA Observations and the GEOS Model

NASA Technical Reports Server (NTRS)

Pawson, Steven; Gelaro, Ron; Ott, Lesley; Putman, Bill; Chatterjee, Abhishek; Koster, Randy; Lee, Eunjee; Oda, Tom; Weir, Brad; Zeng, Fanwei

2018-01-01

The Goddard Earth Observing System (GEOS) model has been developed in the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center. From its roots in chemical transport and as a General Circulation Model, the GEOS model has been extended to an Earth System Model based on a modular construction using the Earth System Modeling Framework (ESMF), combining elements developed in house in the GMAO with others that are imported through collaborative research. It is used extensively for research and for product generation, both as a free-running model and as the core of the GMAO's data assimilation system. In recent years, the GMAO's modeling and assimilation efforts have been strongly supported by Piers Sellers, building on both his earlier legacy as an observationally oriented model developer and his post-astronaut career as a dynamic leader into new territory. Piers' long-standing interest in the carbon cycle and the combination of models with observations motivates this presentation, which will focus on the representation of the carbon cycle in the GEOS Earth System Model. Examples will include: (i) the progression from specified land-atmosphere surface fluxes to computations with an interactive model component (Catchment-CN), along with constraints on vegetation distributions using satellite observations; (ii) the use of high-resolution satellite observations to constrain human-generated inputs to the atmosphere; (iii) studies of the consistency of the observed atmospheric carbon dioxide concentrations with those in the model simulations. The presentation will focus on year-to-year variations in elements of the carbon cycle, specifically on how the observations can inform the representation of mechanisms in the model and lead to integrity in global carbon dioxide simulations. Further, applications of the GEOS model to the planning of new carbon-climate observations will be addressed, as an example of the work that was strongly supported by

Building entity models through observation and learning

NASA Astrophysics Data System (ADS)

Garcia, Richard; Kania, Robert; Fields, MaryAnne; Barnes, Laura

2011-05-01

To support the missions and tasks of mixed robotic/human teams, future robotic systems will need to adapt to the dynamic behavior of both teammates and opponents. One of the basic elements of this adaptation is the ability to exploit both long and short-term temporal data. This adaptation allows robotic systems to predict/anticipate, as well as influence, future behavior for both opponents and teammates and will afford the system the ability to adjust its own behavior in order to optimize its ability to achieve the mission goals. This work is a preliminary step in the effort to develop online entity behavior models through a combination of learning techniques and observations. As knowledge is extracted from the system through sensor and temporal feedback, agents within the multi-agent system attempt to develop and exploit a basic movement model of an opponent. For the purpose of this work, extraction and exploitation is performed through the use of a discretized two-dimensional game. The game consists of a predetermined number of sentries attempting to keep an unknown intruder agent from penetrating their territory. The sentries utilize temporal data coupled with past opponent observations to hypothesize the probable locations of the opponent and thus optimize their guarding locations.

Constraints on High Northern Photosynthesis Increase Using Earth System Models and a Set of Independent Observations

NASA Astrophysics Data System (ADS)

Winkler, A. J.; Brovkin, V.; Myneni, R.; Alexandrov, G.

2017-12-01

Plant growth in the northern high latitudes benefits from increasing temperature (radiative effect) and CO2 fertilization as a consequence of rising atmospheric CO2 concentration. This enhanced gross primary production (GPP) is evident in large scale increase in summer time greening over the 36-year record of satellite observations. In this time period also various global ecosystem models simulate a greening trend in terms of increasing leaf area index (LAI). We also found a persistent greening trend analyzing historical simulations of Earth system models (ESM) participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). However, these models span a large range in strength of the LAI trend, expressed as sensitivity to both key environmental factors, temperature and CO2 concentration. There is also a wide spread in magnitude of the associated increase of terrestrial GPP among the ESMs, which contributes to pronounced uncertainties in projections of future climate change. Here we demonstrate that there is a linear relationship across the CMIP5 model ensemble between projected GPP changes and historical LAI sensitivity, which allows using the observed LAI sensitivity as an "emerging constraint" on GPP estimation at future CO2 concentration. This constrained estimate of future GPP is substantially higher than the traditional multi-model mean suggesting that the majority of current ESMs may be significantly underestimating carbon fixation by vegetation in NHL. We provide three independent lines of evidence in analyzing observed and simulated CO2 amplitude as well as atmospheric CO2 inversion products to arrive at the same conclusion.

Development of KIAPS Observation Processing Package for Data Assimilation System

NASA Astrophysics Data System (ADS)

Kang, Jeon-Ho; Chun, Hyoung-Wook; Lee, Sihye; Han, Hyun-Jun; Ha, Su-Jin

2015-04-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. Data assimilation team at KIAPS has been developing the observation processing system (KIAPS Package for Observation Processing: KPOP) to provide optimal observations to the data assimilation system for the KIAPS Global Model (KIAPS Integrated Model - Spectral Element method based on HOMME: KIM-SH). Currently, the KPOP is capable of processing the satellite radiance data (AMSU-A, IASI), GPS Radio Occultation (GPS-RO), AIRCRAFT (AMDAR, AIREP, and etc…), and synoptic observation (SONDE and SURFACE). KPOP adopted Radiative Transfer for TOVS version 10 (RTTOV_v10) to get brightness temperature (TB) for each channel at top of the atmosphere (TOA), and Radio Occultation Processing Package (ROPP) 1-dimensional forward module to get bending angle (BA) at each tangent point. The observation data are obtained from the KMA which has been composited with BUFR format to be converted with ODB that are used for operational data assimilation and monitoring at the KMA. The Unified Model (UM), Community Atmosphere - Spectral Element (CAM-SE) and KIM-SH model outputs are used for the bias correction (BC) and quality control (QC) of the observations, respectively. KPOP provides radiance and RO data for Local Ensemble Transform Kalman Filter (LETKF) and also provides SONDE, SURFACE and AIRCRAFT data for Three-Dimensional Variational Assimilation (3DVAR). We are expecting all of the observation type which processed in KPOP could be combined with both of the data assimilation method as soon as possible. The preliminary results from each observation type will be introduced with the current development status of the KPOP.

Technical report series on global modeling and data assimilation. Volume 1: Documentation of the Goddard Earth Observing System (GEOS) General Circulation Model, version 1

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Takacs, Lawrence L.; Molod, Andrea; Wang, Tina

1994-01-01

This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

NASA Astrophysics Data System (ADS)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

NASA Technical Reports Server (NTRS)

Estes, Sue; Haynes, John; Omar, Ali

2013-01-01

Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

NASA Technical Reports Server (NTRS)

Estes, Sue; Haynes, John; Omar, Ali

2012-01-01

Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

Reduced-Rank Array Modes of the California Current Observing System

NASA Astrophysics Data System (ADS)

Moore, Andrew M.; Arango, Hernan G.; Edwards, Christopher A.

2018-01-01

The information content of the ocean observing array spanning the U.S. west coast is explored using the reduced-rank array modes (RAMs) derived from a four-dimensional variational (4D-Var) data assimilation system covering a period of three decades. RAMs are an extension of the original formulation of array modes introduced by Bennett (1985) but in the reduced model state-space explored by the 4D-Var system, and reveal the extent to which this space is activated by the observations. The projection of the RAMs onto the empirical orthogonal functions (EOFs) of the 4D-Var background error correlation matrix provides a quantitative measure of the effectiveness of the measurements in observing the circulation. It is found that much of the space spanned by the background error covariance is unconstrained by the present ocean observing system. The RAM spectrum is also used to introduce a new criterion to prevent 4D-Var from overfitting the model to the observations.

Earth observing system instrument pointing control modeling for polar orbiting platforms

NASA Technical Reports Server (NTRS)

Briggs, H. C.; Kia, T.; Mccabe, S. A.; Bell, C. E.

1987-01-01

An approach to instrument pointing control performance assessment for large multi-instrument platforms is described. First, instrument pointing requirements and reference platform control systems for the Eos Polar Platforms are reviewed. Performance modeling tools including NASTRAN models of two large platforms, a modal selection procedure utilizing a balanced realization method, and reduced order platform models with core and instrument pointing control loops added are then described. Time history simulations of instrument pointing and stability performance in response to commanded slewing of adjacent instruments demonstrates the limits of tolerable slew activity. Simplified models of rigid body responses are also developed for comparison. Instrument pointing control methods required in addition to the core platform control system to meet instrument pointing requirements are considered.

A distributed analysis and visualization system for model and observational data

NASA Technical Reports Server (NTRS)

Wilhelmson, Robert B.

1994-01-01

Software was developed with NASA support to aid in the analysis and display of the massive amounts of data generated from satellites, observational field programs, and from model simulations. This software was developed in the context of the PATHFINDER (Probing ATmospHeric Flows in an Interactive and Distributed EnviRonment) Project. The overall aim of this project is to create a flexible, modular, and distributed environment for data handling, modeling simulations, data analysis, and visualization of atmospheric and fluid flows. Software completed with NASA support includes GEMPAK analysis, data handling, and display modules for which collaborators at NASA had primary responsibility, and prototype software modules for three-dimensional interactive and distributed control and display as well as data handling, for which NSCA was responsible. Overall process control was handled through a scientific and visualization application builder from Silicon Graphics known as the Iris Explorer. In addition, the GEMPAK related work (GEMVIS) was also ported to the Advanced Visualization System (AVS) application builder. Many modules were developed to enhance those already available in Iris Explorer including HDF file support, improved visualization and display, simple lattice math, and the handling of metadata through development of a new grid datatype. Complete source and runtime binaries along with on-line documentation is available via the World Wide Web at: http://redrock.ncsa.uiuc.edu/ PATHFINDER/pathre12/top/top.html.

Comparing models of star formation simulating observed interacting galaxies

NASA Astrophysics Data System (ADS)

Quiroga, L. F.; Muñoz-Cuartas, J. C.; Rodrigues, I.

2017-07-01

In this work, we make a comparison between different models of star formation to reproduce observed interacting galaxies. We use observational data to model the evolution of a pair of galaxies undergoing a minor merger. Minor mergers represent situations weakly deviated from the equilibrium configuration but significant changes in star fomation (SF) efficiency can take place, then, minor mergers provide an unique scene to study SF in galaxies in a realistic but yet simple way. Reproducing observed systems also give us the opportunity to compare the results of the simulations with observations, which at the end can be used as probes to characterize the models of SF implemented in the comparison. In this work we compare two different star formation recipes implemented in Gadget3 and GIZMO codes. Both codes share the same numerical background, and differences arise mainly in the star formation recipe they use. We use observations from Pico dos Días and GEMINI telescopes and show how we use observational data of the interacting pair in AM2229-735 to characterize the interacting pair. Later we use this information to simulate the evolution of the system to finally reproduce the observations: Mass distribution, morphology and main features of the merger-induced star formation burst. We show that both methods manage to reproduce roughly the star formation activity. We show, through a careful study, that resolution plays a major role in the reproducibility of the system. In that sense, star formation recipe implemented in GIZMO code has shown a more robust performance. Acknowledgements: This work is supported by Colciencias, Doctorado Nacional - 617 program.

Obs4MIPS: Satellite Observations for Model Evaluation

NASA Astrophysics Data System (ADS)

Ferraro, R.; Waliser, D. E.; Gleckler, P. J.

2017-12-01

This poster will review the current status of the obs4MIPs project, whose purpose is to provide a limited collection of well-established and documented datasets for comparison with Earth system models (https://www.earthsystemcog.org/projects/obs4mips/). These datasets have been reformatted to correspond with the CMIP5 model output requirements, and include technical documentation specifically targeted for their use in model output evaluation. The project holdings now exceed 120 datasets with observations that directly correspond to CMIP5 model output variables, with new additions in response to the CMIP6 experiments. With the growth in climate model output data volume, it is increasing more difficult to bring the model output and the observations together to do evaluations. The positioning of the obs4MIPs datasets within the Earth System Grid Federation (ESGF) allows for the use of currently available and planned online tools within the ESGF to perform analysis using model output and observational datasets without necessarily downloading everything to a local workstation. This past year, obs4MIPs has updated its submission guidelines to closely align with changes in the CMIP6 experiments, and is implementing additional indicators and ancillary data to allow users to more easily determine the efficacy of an obs4MIPs dataset for specific evaluation purposes. This poster will present the new guidelines and indicators, and update the list of current obs4MIPs holdings and their connection to the ESGF evaluation and analysis tools currently available, and being developed for the CMIP6 experiments.

Data-mining analysis of the global distribution of soil carbon in observational databases and Earth system models

NASA Astrophysics Data System (ADS)

Hashimoto, Shoji; Nanko, Kazuki; Ťupek, Boris; Lehtonen, Aleksi

2017-03-01

Future climate change will dramatically change the carbon balance in the soil, and this change will affect the terrestrial carbon stock and the climate itself. Earth system models (ESMs) are used to understand the current climate and to project future climate conditions, but the soil organic carbon (SOC) stock simulated by ESMs and those of observational databases are not well correlated when the two are compared at fine grid scales. However, the specific key processes and factors, as well as the relationships among these factors that govern the SOC stock, remain unclear; the inclusion of such missing information would improve the agreement between modeled and observational data. In this study, we sought to identify the influential factors that govern global SOC distribution in observational databases, as well as those simulated by ESMs. We used a data-mining (machine-learning) (boosted regression trees - BRT) scheme to identify the factors affecting the SOC stock. We applied BRT scheme to three observational databases and 15 ESM outputs from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and examined the effects of 13 variables/factors categorized into five groups (climate, soil property, topography, vegetation, and land-use history). Globally, the contributions of mean annual temperature, clay content, carbon-to-nitrogen (CN) ratio, wetland ratio, and land cover were high in observational databases, whereas the contributions of the mean annual temperature, land cover, and net primary productivity (NPP) were predominant in the SOC distribution in ESMs. A comparison of the influential factors at a global scale revealed that the most distinct differences between the SOCs from the observational databases and ESMs were the low clay content and CN ratio contributions, and the high NPP contribution in the ESMs. The results of this study will aid in identifying the causes of the current mismatches between observational SOC databases and ESM outputs

The Influence of Observation Errors on Analysis Error and Forecast Skill Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, N. C.; Errico, R. M.; Tai, K.-S.

2013-01-01

The Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework is used to explore the response of analysis error and forecast skill to observation quality. In an OSSE, synthetic observations may be created that have much smaller error than real observations, and precisely quantified error may be applied to these synthetic observations. Three experiments are performed in which synthetic observations with magnitudes of applied observation error that vary from zero to twice the estimated realistic error are ingested into the Goddard Earth Observing System Model (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation for a one-month period representing July. The analysis increment and observation innovation are strongly impacted by observation error, with much larger variances for increased observation error. The analysis quality is degraded by increased observation error, but the change in root-mean-square error of the analysis state is small relative to the total analysis error. Surprisingly, in the 120 hour forecast increased observation error only yields a slight decline in forecast skill in the extratropics, and no discernable degradation of forecast skill in the tropics.

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

Dynamical models to explain observations with SPHERE in planetary systems with double debris belts

NASA Astrophysics Data System (ADS)

Lazzoni, C.; Desidera, S.; Marzari, F.; Boccaletti, A.; Langlois, M.; Mesa, D.; Gratton, R.; Kral, Q.; Pawellek, N.; Olofsson, J.; Bonnefoy, M.; Chauvin, G.; Lagrange, A. M.; Vigan, A.; Sissa, E.; Antichi, J.; Avenhaus, H.; Baruffolo, A.; Baudino, J. L.; Bazzon, A.; Beuzit, J. L.; Biller, B.; Bonavita, M.; Brandner, W.; Bruno, P.; Buenzli, E.; Cantalloube, F.; Cascone, E.; Cheetham, A.; Claudi, R. U.; Cudel, M.; Daemgen, S.; De Caprio, V.; Delorme, P.; Fantinel, D.; Farisato, G.; Feldt, M.; Galicher, R.; Ginski, C.; Girard, J.; Giro, E.; Janson, M.; Hagelberg, J.; Henning, T.; Incorvaia, S.; Kasper, M.; Kopytova, T.; LeCoroller, H.; Lessio, L.; Ligi, R.; Maire, A. L.; Ménard, F.; Meyer, M.; Milli, J.; Mouillet, D.; Peretti, S.; Perrot, C.; Rouan, D.; Samland, M.; Salasnich, B.; Salter, G.; Schmidt, T.; Scuderi, S.; Sezestre, E.; Turatto, M.; Udry, S.; Wildi, F.; Zurlo, A.

2018-03-01

circular or eccentric orbit. We then consider multi-planetary systems: two and three equal-mass planets on circular orbits and two equal-mass planets on eccentric orbits in a packed configuration. As a final step, we compare each couple of values (Mp, ap), derived from the dynamical analysis of single and multiple planetary models, with the detection limits obtained with SPHERE. Results: For one single planet on a circular orbit we obtain conclusive results that allow us to exclude such a hypothesis since in most cases this configuration requires massive planets which should have been detected by our observations. Unsatisfactory is also the case of one single planet on an eccentric orbit for which we obtained high masses and/or eccentricities which are still at odds with observations. Introducing multi planetary architectures is encouraging because for the case of three packed equal-mass planets on circular orbits we obtain quite low masses for the perturbing planets which would remain undetected by our SPHERE observations. The case of two equal-mass planets on eccentric orbits is also of interest since it suggests the possible presence of planets with masses lower than the detection limits and with moderate eccentricity. Our results show that the apparent lack of planets in gaps between double belts could be explained by the presence of a system of two or more planets possibly of low mass and on eccentric orbits whose sizes are below the present detection limits. Based on observations collected at Paranal Observatory, ESO (Chile) Program ID: 095.C-0298, 096.C-0241, 097.C-0865, and 198.C-0209.

Correlation between human observer performance and model observer performance in differential phase contrast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ke; Garrett, John; Chen, Guang-Hong

2013-11-15

Purpose: With the recently expanding interest and developments in x-ray differential phase contrast CT (DPC-CT), the evaluation of its task-specific detection performance and comparison with the corresponding absorption CT under a given radiation dose constraint become increasingly important. Mathematical model observers are often used to quantify the performance of imaging systems, but their correlations with actual human observers need to be confirmed for each new imaging method. This work is an investigation of the effects of stochastic DPC-CT noise on the correlation of detection performance between model and human observers with signal-known-exactly (SKE) detection tasks.Methods: The detectabilities of different objectsmore » (five disks with different diameters and two breast lesion masses) embedded in an experimental DPC-CT noise background were assessed using both model and human observers. The detectability of the disk and lesion signals was then measured using five types of model observers including the prewhitening ideal observer, the nonprewhitening (NPW) observer, the nonprewhitening observer with eye filter and internal noise (NPWEi), the prewhitening observer with eye filter and internal noise (PWEi), and the channelized Hotelling observer (CHO). The same objects were also evaluated by four human observers using the two-alternative forced choice method. The results from the model observer experiment were quantitatively compared to the human observer results to assess the correlation between the two techniques.Results: The contrast-to-detail (CD) curve generated by the human observers for the disk-detection experiments shows that the required contrast to detect a disk is inversely proportional to the square root of the disk size. Based on the CD curves, the ideal and NPW observers tend to systematically overestimate the performance of the human observers. The NPWEi and PWEi observers did not predict human performance well either, as the slopes of

Interpreting Field-based Observations of Complex Fluvial System Behavior through Theory and Numerical Models: Examples from the Ganges-Brahmaputra-Meghna Delta

NASA Astrophysics Data System (ADS)

Sincavage, R.; Goodbred, S. L., Jr.; Pickering, J.; Diamond, M. S.; Paola, C.; Liang, M.

2016-12-01

Field observations of depositional systems using outcrop, borehole, and geophysical data stimulate ideas regarding process-based creation of the sedimentary record. Theory and numerical modeling provide insight into the often perplexing nature of these systems by isolating the processes responsible for the observed response. An extensive dataset of physical and chemical sediment properties from field data in the Ganges-Brahmaputra-Meghna Delta (GBMD) indicate the presence of complex, multi-dimensional fluvial system behaviors. Paleodischarges during the last lowstand were insufficient to generate paleovalley geometries and transport boulder-sized basal gravel as observed in densely-spaced (3-5 km) borehole data and a 255 km long fluvial multichannel seismic survey. Instead, uniform flow-derived flood heights and Shields-derived flow velocities based on measured field observations support the conclusion that previously documented megafloods conveyed through the Tsangpo Gorge created the antecedent topography upon which the Holocene sediment dispersal system has since evolved. In the fault-bounded Sylhet Basin east of the main valley system, borehole data reveal three principal mid-Holocene sediment delivery pathways; two that terminate in the basin interior and exhibit rapid mass extraction, and one located along the western margin of Sylhet Basin that serves to bypass the basin interior to downstream depocenters. In spite of topographically favorable conditions and enhanced subsidence rates for delivery into the basin, the fluvial system has favored the bypass-dominated pathway, leaving the central basin perennially underfilled. A "hydrologic barrier" effect from seasonally high monsoon-lake levels has been proposed as a mechanism that precludes sediment delivery to Sylhet Basin. However, numerical models with varying lake level heights indicate that the presence or absence of a seasonal lake has little effect on channel path selection. Rather, it appears that pre

The COSPAR roadmap on Space-based observation and Integrated Earth System Science for 2016-2025

NASA Astrophysics Data System (ADS)

Fellous, Jean-Louis

2016-07-01

The Committee on Space Research of the International Council for Science recently commissioned a study group to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. The paper will provide an overview of the content of the roadmap. All types of observation are considered in the roadmap, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced in the roadmap. Instances are given of present types of observation, what is already on the roadmap for 2016-2025 and some of the issues to be faced. The current status and prospects for Earth-system modelling are summarized. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Finally the roadmap offers a set of concluding discussions covering general developmental needs, requirements for continuity of

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution smaller than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have some first images that demonstrate the most innovative capability from EOS Terra: MODIS - 1.37 microns cirrus channel; 250 m daily cover for clouds and vegetation change; 7 solar channels for land and aerosol; new fire channels; Chlorophyll fluorescence; MISR - 9 multi angle views of clouds and vegetation; MOPITT - Global CO maps and CH4 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

The involvement of model-based but not model-free learning signals during observational reward learning in the absence of choice.

PubMed

Dunne, Simon; D'Souza, Arun; O'Doherty, John P

2016-06-01

A major open question is whether computational strategies thought to be used during experiential learning, specifically model-based and model-free reinforcement learning, also support observational learning. Furthermore, the question of how observational learning occurs when observers must learn about the value of options from observing outcomes in the absence of choice has not been addressed. In the present study we used a multi-armed bandit task that encouraged human participants to employ both experiential and observational learning while they underwent functional magnetic resonance imaging (fMRI). We found evidence for the presence of model-based learning signals during both observational and experiential learning in the intraparietal sulcus. However, unlike during experiential learning, model-free learning signals in the ventral striatum were not detectable during this form of observational learning. These results provide insight into the flexibility of the model-based learning system, implicating this system in learning during observation as well as from direct experience, and further suggest that the model-free reinforcement learning system may be less flexible with regard to its involvement in observational learning. Copyright © 2016 the American Physiological Society.

Towards a regional coastal ocean observing system: An initial design for the Southeast Coastal Ocean Observing Regional Association

NASA Astrophysics Data System (ADS)

Seim, H. E.; Fletcher, M.; Mooers, C. N. K.; Nelson, J. R.; Weisberg, R. H.

2009-05-01

A conceptual design for a southeast United States regional coastal ocean observing system (RCOOS) is built upon a partnership between institutions of the region and among elements of the academic, government and private sectors. This design envisions support of a broad range of applications (e.g., marine operations, natural hazards, and ecosystem-based management) through the routine operation of predictive models that utilize the system observations to ensure their validity. A distributed information management system enables information flow, and a centralized information hub serves to aggregate information regionally and distribute it as needed. A variety of observing assets are needed to satisfy model requirements. An initial distribution of assets is proposed that recognizes the physical structure and forcing in the southeast U.S. coastal ocean. In-situ data collection includes moorings, profilers and gliders to provide 3D, time-dependent sampling, HF radar and surface drifters for synoptic sampling of surface currents, and satellite remote sensing of surface ocean properties. Nested model systems are required to properly represent ocean conditions from the outer edge of the EEZ to the watersheds. An effective RCOOS will depend upon a vital "National Backbone" (federally supported) system of in situ and satellite observations, model products, and data management. This dependence highlights the needs for a clear definition of the National Backbone components and a Concept of Operations (CONOPS) that defines the roles, functions and interactions of regional and federal components of the integrated system. A preliminary CONOPS is offered for the Southeast (SE) RCOOS. Thorough system testing is advocated using a combination of application-specific and process-oriented experiments. Estimates of costs and personnel required as initial components of the SE RCOOS are included. Initial thoughts on the Research and Development program required to support the RCOOS are

Observation model and parameter partials for the JPL geodetic GPS modeling software GPSOMC

NASA Technical Reports Server (NTRS)

Sovers, O. J.; Border, J. S.

1988-01-01

The physical models employed in GPSOMC and the modeling module of the GIPSY software system developed at JPL for analysis of geodetic Global Positioning Satellite (GPS) measurements are described. Details of the various contributions to range and phase observables are given, as well as the partial derivatives of the observed quantities with respect to model parameters. A glossary of parameters is provided to enable persons doing data analysis to identify quantities in the current report with their counterparts in the computer programs. There are no basic model revisions, with the exceptions of an improved ocean loading model and some new options for handling clock parametrization. Such misprints as were discovered were corrected. Further revisions include modeling improvements and assurances that the model description is in accord with the current software.

A gunner model for an AAA tracking task with interrupted observations

NASA Technical Reports Server (NTRS)

Yu, C. F.; Wei, K. C.; Vikmanis, M.

1982-01-01

The problem of modeling a trained human operator's tracking performance in an anti-aircraft system under various display blanking conditions is discussed. The input to the gunner is the observable tracking error subjected to repeated interruptions (blanking). A simple and effective gunner model was developed. The effect of blanking on the gunner's tracking performance is approached via modeling the observer and controller gains.

Mesoscale weather and climate modeling with the global non-hydrostatic Goddard Earth Observing System Model (GEOS-5) at cloud-permitting resolutions

NASA Astrophysics Data System (ADS)

Putman, W. M.; Suarez, M.

2009-12-01

The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.

Thermal Infrared Observations and Thermophysical Modeling of Phobos

NASA Astrophysics Data System (ADS)

Smith, Nathan Michael; Edwards, Christopher Scott; Mommert, Michael; Trilling, David E.; Glotch, Timothy

2016-10-01

Mars-observing spacecraft have the opportunity to study Phobos from Mars orbit, and have produced a sizeable record of observations using the same instruments that study the surface of the planet below. However, these observations are generally infrequent, acquired only rarely over each mission.Using observations gathered by Mars Global Surveyor's (MGS) Thermal Emission Spectrometer (TES), we can investigate the fine layer of regolith that blankets Phobos' surface, and characterize its thermal properties. The mapping of TES observations to footprints on the Phobos surface has not previously been undertaken, and must consider the orientation and position of both MGS and Phobos, and TES's pointing mirror angle. Approximately 300 fully resolved observations are available covering a significant subset of Phobos' surface at a variety of scales.The properties of the surface regolith, such as grain size, density, and conductivity, determine how heat is absorbed, transferred, and reradiated to space. Thermophysical modeling allows us to simulate these processes and predict, for a given set of assumed parameters, how the observed thermal infrared spectra will appear. By comparing models to observations, we can constrain the properties of the regolith, and see how these properties vary with depth, as well as regionally across the Phobos surface. These constraints are key to understanding how Phobos formed and evolved over time, which in turn will help inform the environment and processes that shaped the solar system as a whole.We have developed a thermophysical model of Phobos adapted from a model used for unresolved observations of asteroids. The model has been modified to integrate thermal infrared flux across each observed portion of Phobos. It will include the effects of surface roughness, temperature-dependent conductivity, as well as radiation scattered, reflected, and thermally emitted from the Martian surface. Combining this model with the newly-mapped TES

The Group on Earth Observations and the Global Earth Observation System of Systems

NASA Astrophysics Data System (ADS)

Achache, J.

2006-05-01

The Group on Earth Observations (GEO) is leading a worldwide effort to build a Global Earth Observation System of Systems (GEOSS) over the next 10 years. The GEOSS vision, articulated in its 10-Year Implementation Plan, represents the consolidation of a global scientific and political consensus: the assessment of the state of the Earth requires continuous and coordinated observation of our planet at all scales. GEOSS aims to achieve comprehensive, coordinated and sustained observations of the Earth system in order to improve monitoring of the state of the Earth; increase understanding of Earth processes; and enhance prediction of the behaviour of the Earth system. After the World Summit on Sustainable Development in 2002 highlighted the urgent need for coordinated observations relating to the state of the Earth, GEO was established at the Third Earth Observation Summit in February 2005 and the GEOSS 10-Year Implementation Plan was endorsed. GEO currently involves 60 countries; the European Commission; and 43 international organizations and has begun implementation of the GEOSS 10-Year Implementation Plan. GEO programme activities cover nine societal benefit areas (Disasters; Health; Energy; Climate; Water; Weather; Ecosystems; Agriculture; Biodiversity) and five transverse or crosscutting elements (User Engagement; Architecture; Data Management; Capacity Building; Outreach). All these activities have as their final goal the establishment of the "system of systems" which will yield a broad range of basic societal benefits, including the reduction of loss of life and property from tsunamis, hurricanes, and other natural disasters; improved water resource and energy management; and improved understanding of environmental factors significant to public health. As a "system of systems", GEOSS will work with and build upon existing national, regional, and international systems to provide comprehensive, coordinated Earth observations from thousands of instruments worldwide

Thermospheric Mass Density Specification: Synthesis of Observations and Models

DTIC Science & Technology

2013-10-21

Simulation Experiments (OSSEs) of the column-integrated ratio of atomic oxygen and molecular nitrogen. Note that OSSEs assimilate, for a given...realistic observing system, synthetically generated observational data often sampled from model simulation results, in place of actually observed values...and molecular oxygen mass mixing ratio). Note that in the TIEGCM the molecular nitrogen mass mixing ratio is specified so that the sum of mixing

Developing Vocabularies to Improve Understanding and Use of NOAA Observing Systems

NASA Astrophysics Data System (ADS)

Austin, M.

2014-12-01

The NOAA Observing System Integrated Analysis project (NOSIA II), is an attempt to capture and tell the story of how valuable observing systems are in producing products and services that are required to fulfill the NOAA's diverse mission. NOAA's goals and mission areas cover a broad range of environmental data; a complexity exists in terms and vocabulary as applied to the creation of observing system derived products. The NOSIA data collection focused first on decomposing NOAA's goals in the creation and acceptance of Mission Service Areas (MSAs) by NOAA senior leadership. Products and services that supported the MSAs were then identified through the process of interviewing product producers across NOAA organization. Product Data inputs including models, databases and observing system were also identified. The NOSIA model contains over 20,000 nodes each representing levels in a network connecting products, datasources, users and desired outcomes. An immediate need became apparent that the complexity and variety of the data collected required data management to mature the quality and the content of the NOSIA model. The NOSIA Analysis Database (ADB) was developed initially to improve consistency of terms and data types to allow for the linkage of observing systems, products and NOAA's Goals and mission. The ADB also allowed for the prototyping of reports and product generation in an easily accessible and comprehensive format for the first time. Web based visualization of relationships between products, datasources, users, producers were generated to make the information easily understood This includes developing ontologies/vocabularies that are used for the development of users type specific products for NOAA leadership, Observing System Portfolio mangers and the users of NOAA data.

Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0

NASA Astrophysics Data System (ADS)

Schürmann, Gregor J.; Kaminski, Thomas; Köstler, Christoph; Carvalhais, Nuno; Voßbeck, Michael; Kattge, Jens; Giering, Ralf; Rödenbeck, Christian; Heimann, Martin; Zaehle, Sönke

2016-09-01

We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS) built around the tangent-linear version of the JSBACH land-surface scheme, which is part of the MPI-Earth System Model v1. The simulated phenology and net land carbon balance were constrained by globally distributed observations of the fraction of absorbed photosynthetically active radiation (FAPAR, using the TIP-FAPAR product) and atmospheric CO2 at a global set of monitoring stations for the years 2005 to 2009. When constrained by FAPAR observations alone, the system successfully, and computationally efficiently, improved simulated growing-season average FAPAR, as well as its seasonality in the northern extra-tropics. When constrained by atmospheric CO2 observations alone, global net and gross carbon fluxes were improved, despite a tendency of the system to underestimate tropical productivity. Assimilating both data streams jointly allowed the MPI-CCDAS to match both observations (TIP-FAPAR and atmospheric CO2) equally well as the single data stream assimilation cases, thereby increasing the overall appropriateness of the simulated biosphere dynamics and underlying parameter values. Our study thus demonstrates the value of multiple-data-stream assimilation for the simulation of terrestrial biosphere dynamics. It further highlights the potential role of remote sensing data, here the TIP-FAPAR product, in stabilising the strongly underdetermined atmospheric inversion problem posed by atmospheric transport and CO2 observations alone. Notwithstanding these advances, the constraint of the observations on regional gross and net CO2 flux patterns on the MPI-CCDAS is limited through the coarse-scale parametrisation of the biosphere model. We expect improvement through a refined initialisation strategy and inclusion of further biosphere observations as constraints.

The Coastal Observing System for Northern and Arctic Seas (COSYNA)

NASA Astrophysics Data System (ADS)

Baschek, Burkard; Schroeder, Friedhelm; Brix, Holger; Riethmüller, Rolf; Badewien, Thomas H.; Breitbach, Gisbert; Brügge, Bernd; Colijn, Franciscus; Doerffer, Roland; Eschenbach, Christiane; Friedrich, Jana; Fischer, Philipp; Garthe, Stefan; Horstmann, Jochen; Krasemann, Hajo; Metfies, Katja; Merckelbach, Lucas; Ohle, Nino; Petersen, Wilhelm; Pröfrock, Daniel; Röttgers, Rüdiger; Schlüter, Michael; Schulz, Jan; Schulz-Stellenfleth, Johannes; Stanev, Emil; Staneva, Joanna; Winter, Christian; Wirtz, Kai; Wollschläger, Jochen; Zielinski, Oliver; Ziemer, Friedwart

2017-05-01

The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example of a heavily used coastal area, and Svalbard as an example of an Arctic coast that is under strong pressure due to global change.The COSYNA automated observing and modelling system is designed to monitor real-time conditions and provide short-term forecasts, data, and data products to help assess the impact of anthropogenically induced change. Observations are carried out by combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publicly available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.

The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2

NASA Astrophysics Data System (ADS)

Swales, Dustin J.; Pincus, Robert; Bodas-Salcedo, Alejandro

2018-01-01

The Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) gathers together a collection of observation proxies or satellite simulators that translate model-simulated cloud properties to synthetic observations as would be obtained by a range of satellite observing systems. This paper introduces COSP2, an evolution focusing on more explicit and consistent separation between host model, coupling infrastructure, and individual observing proxies. Revisions also enhance flexibility by allowing for model-specific representation of sub-grid-scale cloudiness, provide greater clarity by clearly separating tasks, support greater use of shared code and data including shared inputs across simulators, and follow more uniform software standards to simplify implementation across a wide range of platforms. The complete package including a testing suite is freely available.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Einaudi, Franco (Technical Monitor)

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution better than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have first images that demonstrate the most innovative capability from EOS Terra 5 instruments: MODIS - 1.37 micron cirrus cloud channel; 250m daily coverage for clouds and vegetation change; 7 solar channels for land and aerosol studies; new fire channels; Chlorophyll fluorescence; MISR - first 9 multi angle views of clouds and vegetation; MOPITT - first global CO maps and C114 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

NASA Technical Reports Server (NTRS)

Mahanama, Sarith P.; Koster, Randal D.; Walker, Gregory K.; Takacs, Lawrence L.; Reichle, Rolf H.; De Lannoy, Gabrielle; Liu, Qing; Zhao, Bin; Suarez, Max J.

2015-01-01

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

Individual Colorimetric Observer Model

PubMed Central

Asano, Yuta; Fairchild, Mark D.; Blondé, Laurent

2016-01-01

This study proposes a vision model for individual colorimetric observers. The proposed model can be beneficial in many color-critical applications such as color grading and soft proofing to assess ranges of color matches instead of a single average match. We extended the CIE 2006 physiological observer by adding eight additional physiological parameters to model individual color-normal observers. These eight parameters control lens pigment density, macular pigment density, optical densities of L-, M-, and S-cone photopigments, and λmax shifts of L-, M-, and S-cone photopigments. By identifying the variability of each physiological parameter, the model can simulate color matching functions among color-normal populations using Monte Carlo simulation. The variabilities of the eight parameters were identified through two steps. In the first step, extensive reviews of past studies were performed for each of the eight physiological parameters. In the second step, the obtained variabilities were scaled to fit a color matching dataset. The model was validated using three different datasets: traditional color matching, applied color matching, and Rayleigh matches. PMID:26862905

Design of a practical model-observer-based image quality assessment method for x-ray computed tomography imaging systems

PubMed Central

Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.

2016-01-01

Abstract. The use of a channelization mechanism on model observers not only makes mimicking human visual behavior possible, but also reduces the amount of image data needed to estimate the model observer parameters. The channelized Hotelling observer (CHO) and channelized scanning linear observer (CSLO) have recently been used to assess CT image quality for detection tasks and combined detection/estimation tasks, respectively. Although the use of channels substantially reduces the amount of data required to compute image quality, the number of scans required for CT imaging is still not practical for routine use. It is our desire to further reduce the number of scans required to make CHO or CSLO an image quality tool for routine and frequent system validations and evaluations. This work explores different data-reduction schemes and designs an approach that requires only a few CT scans. Three different kinds of approaches are included in this study: a conventional CHO/CSLO technique with a large sample size, a conventional CHO/CSLO technique with fewer samples, and an approach that we will show requires fewer samples to mimic conventional performance with a large sample size. The mean value and standard deviation of areas under ROC/EROC curve were estimated using the well-validated shuffle approach. The results indicate that an 80% data reduction can be achieved without loss of accuracy. This substantial data reduction is a step toward a practical tool for routine-task-based QA/QC CT system assessment. PMID:27493982

Observation model and parameter partials for the JPL geodetic (GPS) modeling software 'GPSOMC'

NASA Technical Reports Server (NTRS)

Sovers, O. J.

1990-01-01

The physical models employed in GPSOMC, the modeling module of the GIPSY software system developed at JPL for analysis of geodetic Global Positioning Satellite (GPS) measurements are described. Details of the various contributions to range and phase observables are given, as well as the partial derivatives of the observed quantities with respect to model parameters. A glossary of parameters is provided to enable persons doing data analysis to identify quantities with their counterparts in the computer programs. The present version is the second revision of the original document which it supersedes. The modeling is expanded to provide the option of using Cartesian station coordinates; parameters for the time rates of change of universal time and polar motion are also introduced.

Facilitating the Easy Use of Earth Observation Data in Earth System Models through CyberConnector

NASA Astrophysics Data System (ADS)

Di, L.; Sun, Z.; Zhang, C.

2017-12-01

Earth system models (ESM) are an important tool used to understand the Earth system and predict its future states. On other hand, Earth observations (EO) provides the current state of the system. EO data are very useful in ESM initialization, verification, validation, and inter-comparison. However, EO data often cannot directly be consumed by ESMs because of the syntactic and semantic mismatches between EO products and ESM requirements. In order to remove the mismatches, scientists normally spend long time to customize EO data for ESM consumption. CyberConnector, a NSF EarthCube building block, is intended to automate the data customization so that scientists can be relieved from the laborious EO data customization. CyberConnector uses web-service-based geospatial processing models (GPM) as the mechanism to automatically customize the EO data into the right products in the right form needed by ESMs. It can support many different ESMs through its standard interfaces. It consists of seven modules: GPM designer, GPM binder, GPM runner, GPM monitor, resource register, order manager, and result display. In CyberConnector, EO data instances and GPMs are independent and loosely coupled. A modeler only needs to create a GPM in the GMP designer for EO data customization. Once the modeler specifies a study area, the designed GPM will be activated and take the temporal and spatial extents as constraints to search the data sources and customize the available EO data into the ESM-acceptable form. The execution of GMP is completely automatic. Currently CyberConnector has been fully developed. In order to validate the feasibility, flexibility, and ESM independence of CyberConnector, three ESMs from different geoscience disciplines, including the Cloud-Resolving Model (CRM), the Finite Volume Coastal Ocean Model (FVCOM), and the Community Multiscale Air Quality Model (CMAQ), have been experimented with CyberConnector through closely collaborating with modelers. In the experiment

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

Ground-based Observation System Development for the Moon Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Wang, Yang; Huang, Yu; Wang, Shurong; Li, Zhanfeng; Zhang, Zihui; Hu, Xiuqing; Zhang, Peng

2017-05-01

The Moon provides a suitable radiance source for on-orbit calibration of space-borne optical instruments. A ground-based observation system dedicated to the hyper-spectral radiometry of the Moon has been developed for improving and validating the current lunar model. The observation instrument using a dispersive imaging spectrometer is particularly designed for high-accuracy observations of the lunar radiance. The simulation and analysis of the push-broom mechanism is made in detail for lunar observations, and the automated tracking and scanning is well accomplished in different observational condition. A three-month series of hyper-spectral imaging experiments of the Moon have been performed in the wavelength range from 400 to 1000 nm near Lijiang Observatory (Yunnan, China) at phase angles -83°-87°. Preliminary results and data comparison are presented, and it shows the instrument performance and lunar observation capability of this system are well validated. Beyond previous measurements, this observation system provides the entire lunar disk images of continuous spectral coverage by adopting the push-broom mode with special scanning scheme and leads to the further research of lunar photometric model.

Detecting influential observations in nonlinear regression modeling of groundwater flow

USGS Publications Warehouse

Yager, Richard M.

1998-01-01

Nonlinear regression is used to estimate optimal parameter values in models of groundwater flow to ensure that differences between predicted and observed heads and flows do not result from nonoptimal parameter values. Parameter estimates can be affected, however, by observations that disproportionately influence the regression, such as outliers that exert undue leverage on the objective function. Certain statistics developed for linear regression can be used to detect influential observations in nonlinear regression if the models are approximately linear. This paper discusses the application of Cook's D, which measures the effect of omitting a single observation on a set of estimated parameter values, and the statistical parameter DFBETAS, which quantifies the influence of an observation on each parameter. The influence statistics were used to (1) identify the influential observations in the calibration of a three-dimensional, groundwater flow model of a fractured-rock aquifer through nonlinear regression, and (2) quantify the effect of omitting influential observations on the set of estimated parameter values. Comparison of the spatial distribution of Cook's D with plots of model sensitivity shows that influential observations correspond to areas where the model heads are most sensitive to certain parameters, and where predicted groundwater flow rates are largest. Five of the six discharge observations were identified as influential, indicating that reliable measurements of groundwater flow rates are valuable data in model calibration. DFBETAS are computed and examined for an alternative model of the aquifer system to identify a parameterization error in the model design that resulted in overestimation of the effect of anisotropy on horizontal hydraulic conductivity.

Evaluation of CNN as anthropomorphic model observer

NASA Astrophysics Data System (ADS)

Massanes, Francesc; Brankov, Jovan G.

2017-03-01

Model observers (MO) are widely used in medical imaging to act as surrogates of human observers in task-based image quality evaluation, frequently towards optimization of reconstruction algorithms. In this paper, we explore the use of convolutional neural networks (CNN) to be used as MO. We will compare CNN MO to alternative MO currently being proposed and used such as the relevance vector machine based MO and channelized Hotelling observer (CHO). As the success of the CNN, and other deep learning approaches, is rooted in large data sets availability, which is rarely the case in medical imaging systems task-performance evaluation, we will evaluate CNN performance on both large and small training data sets.

A Novel Observation-Guided Approach for Evaluating Mesoscale Convective Systems Simulated by the DOE ACME Model

NASA Astrophysics Data System (ADS)

Feng, Z.; Ma, P. L.; Hardin, J. C.; Houze, R.

2017-12-01

Mesoscale convective systems (MCSs) are the largest type of convective storms that develop when convection aggregates and induces mesoscale circulation features. Over North America, MCSs contribute over 60% of the total warm-season precipitation and over half of the extreme daily precipitation in the central U.S. Our recent study (Feng et al. 2016) found that the observed increases in springtime total and extreme rainfall in this region are dominated by increased frequency and intensity of long-lived MCSs*. To date, global climate models typically do not run at a resolution high enough to explicitly simulate individual convective elements and may not have adequate process representations for MCSs, resulting in a large deficiency in projecting changes of the frequency of extreme precipitation events in future climate. In this study, we developed a novel observation-guided approach specifically designed to evaluate simulated MCSs in the Department of Energy's climate model, Accelerated Climate Modeling for Energy (ACME). The ACME model has advanced treatments for convection and subgrid variability and for this study is run at 25 km and 100 km grid spacings. We constructed a robust MCS database consisting of over 500 MCSs from 3 warm-season observations by applying a feature-tracking algorithm to 4-km resolution merged geostationary satellite and 3-D NEXRAD radar network data over the Continental US. This high-resolution MCS database is then down-sampled to the 25 and 100 km ACME grids to re-characterize key MCS properties. The feature-tracking algorithm is adapted with the adjusted characteristics to identify MCSs from ACME model simulations. We demonstrate that this new analysis framework is useful for evaluating ACME's warm-season precipitation statistics associated with MCSs, and provides insights into the model process representations related to extreme precipitation events for future improvement. *Feng, Z., L. R. Leung, S. Hagos, R. A. Houze, C. D. Burleyson

Starbursts in interacting galaxies: Observations and models

NASA Technical Reports Server (NTRS)

Bernloehr, Konrad

1990-01-01

Starbursts have been a puzzling field of research for more than a decade. It is evident that they played a significant role in the evolution of many galaxies but still quite little is known about the starburst mechanisms. A way towards a better interpretation of the available data is the comparison with evolution models of starburst. The modelling of starbursts and the fitting of such model starbursts to observed data is discussed. The models were applied to a subset of starburst and post-starburst galaxies in a sample of 30 interacting systems. These galaxies are not ultraluminous far infrared (FIR) galaxies but rather ordinary starburst galaxies with FIR luminosities of a few 10(exp 10) to a few 10(exp 11) solar luminosities.

The Earth Phenomena Observing System: Intelligent Autonomy for Satellite Operations

NASA Technical Reports Server (NTRS)

Ricard, Michael; Abramson, Mark; Carter, David; Kolitz, Stephan

2003-01-01

Earth monitoring systems of the future may include large numbers of inexpensive small satellites, tasked in a coordinated fashion to observe both long term and transient targets. For best performance, a tool which helps operators optimally assign targets to satellites will be required. We present the design of algorithms developed for real-time optimized autonomous planning of large numbers of small single-sensor Earth observation satellites. The algorithms will reduce requirements on the human operators of such a system of satellites, ensure good utilization of system resources, and provide the capability to dynamically respond to temporal terrestrial phenomena. Our initial real-time system model consists of approximately 100 satellites and large number of points of interest on Earth (e.g., hurricanes, volcanoes, and forest fires) with the objective to maximize the total science value of observations over time. Several options for calculating the science value of observations include the following: 1) total observation time, 2) number of observations, and the 3) quality (a function of e.g., sensor type, range, slant angle) of the observations. An integrated approach using integer programming, optimization and astrodynamics is used to calculate optimized observation and sensor tasking plans.

The Martian Dust Cycle: Observations and Modeling

NASA Technical Reports Server (NTRS)

Kahre, Melinda A.

2013-01-01

The dust cycle is critically important for Mars' current climate system. Suspended atmospheric dust affects the radiative balance of the atmosphere, and thus greatly influences the thermal and dynamical state of the atmosphere. Evidence for the presence of dust in the Martian atmosphere can be traced back to yellow clouds telescopically observed as early as the early 19th century. The Mariner 9 orbiter arrived at Mars in November of 1971 to find a planet completely enshrouded in airborne dust. Since that time, the exchange of dust between the planet's surface and atmosphere and the role of airborne dust on Mars' weather and climate has been studied using observations and numerical models. The goal of this talk is to give an overview of the observations and to discuss the successes and challenges associated with modeling the dust cycle. Dust raising events on Mars range in size from meters to hundreds of kilometers. During some years, regional storms merge to produce hemispheric or planet encircling dust clouds that obscure the surface and raise atmospheric temperatures by tens of kelvin. The interannual variability of planet encircling dust storms is poorly understood. Although the occurrence and season of large regional and global dust storms are highly variable from one year to the next, there are many features of the dust cycle that occur year after year. A low-level dust haze is maintained during northern spring and summer, while elevated levels of atmospheric dust occur during northern autumn and winter. During years without global-scale dust storms, two peaks in total dust loading are generally observed: one peak occurs before northern winter solstice and one peak occurs after northern winter solstice. Numerical modeling studies attempting to interactively simulate the Martian dust cycle with general circulation models (GCMs) include the lifting, transport, and sedimentation of radiatively active dust. Two dust lifting processes are commonly represented in

Promoting discovery and access to real time observations produced by regional coastal ocean observing systems

NASA Astrophysics Data System (ADS)

Anderson, D. M.; Snowden, D. P.; Bochenek, R.; Bickel, A.

2015-12-01

In the U.S. coastal waters, a network of eleven regional coastal ocean observing systems support real-time coastal and ocean observing. The platforms supported and variables acquired are diverse, ranging from current sensing high frequency (HF) radar to autonomous gliders. The system incorporates data produced by other networks and experimental systems, further increasing the breadth of the collection. Strategies promoted by the U.S. Integrated Ocean Observing System (IOOS) ensure these data are not lost at sea. Every data set deserves a description. ISO and FGDC compliant metadata enables catalog interoperability and record-sharing. Extensive use of netCDF with the Climate and Forecast convention (identifying both metadata and a structured format) is shown to be a powerful strategy to promote discovery, interoperability, and re-use of the data. To integrate specialized data which are often obscure, quality control protocols are being developed to homogenize the QC and make these data more integrate-able. Data Assembly Centers have been established to integrate some specialized streams including gliders, animal telemetry, and HF radar. Subsets of data that are ingested into the National Data Buoy Center are also routed to the Global Telecommunications System (GTS) of the World Meteorological Organization to assure wide international distribution. From the GTS, data are assimilated into now-cast and forecast models, fed to other observing systems, and used to support observation-based decision making such as forecasts, warnings, and alerts. For a few years apps were a popular way to deliver these real-time data streams to phones and tablets. Responsive and adaptive web sites are an emerging flexible strategy to provide access to the regional coastal ocean observations.

Preliminary Results from an Assimilation of TOMS Aerosol Observations Into the GOCART Model

NASA Technical Reports Server (NTRS)

daSilva, Arlindo; Weaver, Clark J.; Ginoux, Paul; Torres, Omar; Einaudi, Franco (Technical Monitor)

2000-01-01

At NASA Goddard we are developing a global aerosol data assimilation system that combines advances in remote sensing and modeling of atmospheric aerosols. The goal is to provide high resolution, 3-D aerosol distributions to the research community. Our first step is to develop a simple assimilation system for Saharan mineral aerosol. The Goddard Chemistry and Aerosol Radiation model (GOCART) provides accurate 3-D mineral aerosol size distributions that compare well with TOMS satellite observations. Surface, mobilization, wet and dry deposition, convective and long-range transport are all driven by assimilated fields from the Goddard Earth Observing System Data Assimilation System, GEOS-DAS. Our version of GOCART transports sizes from.08-10 microns and only simulates Saharan dust. TOMS radiance observations in the ultra violet provide information on the mineral and carbonaceous aerosol fields. We use two main observables in this study: the TOMS aerosol index (AI) which is directly related to the ratio of the 340 and 380 radiances and the 380 radiance. These are sensitive to the aerosol optical thickness, the single scattering albedo and the height of the aerosol layer. The Goddard Aerosol Assimilation System (GAAS) uses the Data Assimilation Office's Physical-space Statistical Analysis System (PSAS) to combine TOMS observations and GOCART model first guess fields. At this initial phase we only assimilate observations into the the GOCART model over regions of Africa and the Atlantic where mineral aerosols dominant and carbonaceous aerosols are minimal, Our preliminary results during summer show that the assimilation with TOMS data modifies both the aerosol mass loading and the single scattering albedo. Assimilated aerosol fields will be compared with assimilated aerosol fields from GOCART and AERONET observations over Cape Verde.

Analysis and modeling of tropical convection observed by CYGNSS

NASA Astrophysics Data System (ADS)

Lang, T. J.; Li, X.; Roberts, J. B.; Mecikalski, J. R.

2017-12-01

The Cyclone Global Navigation Satellite System (CYGNSS) is a multi-satellite constellation that utilizes Global Positioning System (GPS) reflectometry to retrieve near-surface wind speeds over the ocean. While CYGNSS is primarily aimed at measuring wind speeds in tropical cyclones, our research has established that the mission may also provide valuable insight into the relationships between wind-driven surface fluxes and general tropical oceanic convection. Currently, we are examining organized tropical convection using a mixture of CYGNSS level 1 through level 3 data, IMERG (Integrated Multi-satellite Retrievals for Global Precipitation Measurement), and other ancillary datasets (including buoys, GPM level 1 and 2 data, as well as ground-based radar). In addition, observing system experiments (OSEs) are being performed using hybrid three-dimensional variational assimilation to ingest CYGNSS observations into a limited-domain, convection-resolving model. Our focus for now is on case studies of convective evolution, but we will also report on progress toward statistical analysis of convection sampled by CYGNSS. Our working hypothesis is that the typical mature phase of organized tropical convection is marked by the development of a sharp gust-front boundary from an originally spatially broader but weaker wind speed change associated with precipitation. This increase in the wind gradient, which we demonstrate is observable by CYGNSS, likely helps to focus enhanced turbulent fluxes of convection-sustaining heat and moisture near the leading edge of the convective system where they are more easily ingested by the updraft. Progress on the testing and refinement of this hypothesis, using a mixture of observations and modeling, will be reported.

Observers for Systems with Nonlinearities Satisfying an Incremental Quadratic Inequality

NASA Technical Reports Server (NTRS)

Acikmese, Ahmet Behcet; Corless, Martin

2004-01-01

We consider the problem of state estimation for nonlinear time-varying systems whose nonlinearities satisfy an incremental quadratic inequality. These observer results unifies earlier results in the literature; and extend it to some additional classes of nonlinearities. Observers are presented which guarantee that the state estimation error exponentially converges to zero. Observer design involves solving linear matrix inequalities for the observer gain matrices. Results are illustrated by application to a simple model of an underwater.

The meteorology of Gale crater as determined from rover environmental monitoring station observations and numerical modeling. Part I: Comparison of model simulations with observations

NASA Astrophysics Data System (ADS)

Pla-Garcia, Jorge; Rafkin, Scot C. R.; Kahre, Melinda; Gomez-Elvira, Javier; Hamilton, Victoria E.; Navarro, Sara; Torres, Josefina; Marín, Mercedes; Vasavada, Ashwin R.

2016-12-01

Air temperature, ground temperature, pressure, and wind speed and direction data obtained from the Rover Environmental Monitoring Station onboard the Mars Science Laboratory rover Curiosity are compared to data from the Mars Regional Atmospheric Modeling System. A full diurnal cycle at four different seasons (Ls 0, 90, 180 and 270) is investigated at the rover location within Gale crater, Mars. Model results are shown to be in good agreement with observations when considering the uncertainties in the observational data set. The good agreement provides justification for utilizing the model results to investigate the broader meteorological environment of the Gale crater region, which is described in the second, companion paper.

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Interactions of Vegetation and Climate: Remote Observations, Earth System Models, and the Amazon Forest

NASA Astrophysics Data System (ADS)

Quetin, Gregory R.

transitions in sign (greener when warmer or drier to greener when cooler or wetter) along an emergent line in climate space with a slope of about 59 mm/yr/°C, twice as steep as contours of aridity. The mismatch between these slopes is evidence at a global scale of the limitation of both water supply due to inefficiencies in plant access to rainfall, and plant physiological responses to atmospheric water demand. This empirical pattern can provide a functional constraint for process-based models, helping to improve predictions of the global-scale response of vegetation to a changing climate. In Chapter 2, we use observations of vegetation interaction with the physical environment to identify where ecosystem functioning is well simulated in an ensemble of Earth system models. We leverage this data-model comparison to hypothesize which physiological mechanisms--photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability--dominate the ecosystem response in places with different climates. The models are generally successful in reproducing the broad sign and shape of ecosystem function across climate space except for simulating generally lower leaf area during warmer years in places with hot wet climates. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models. Finally, models and observations share an abrupt threshold between dry regions and wet regions where strong positive vegetation response to precipitation falls to nearly zero in places receiving around 1000 mm/year. In Chapter 3, we investigate how ecoclimate interactions change

Gulf of Mexico Coastal Ocean Observing System: The Gulf Component of the U.S. Integrated Ocean Observing System

NASA Astrophysics Data System (ADS)

Bernard, L. J.; Moersdorf, P. F.

2005-05-01

The United States is developing an Integrated Ocean Observing System (IOOS) as the U.S. component of the international Global Ocean Observing System (GOOS). IOOS consists of: (1) a coastal observing system for the U.S. EEZ, estuaries, and Great Lakes; and (2) a contribution to the global component of GOOS focused on climate and maritime services. The coastal component will consist of: (1) a National Backbone of observations and products from our coastal ocean supported by federal agencies; and (2) contributions of Regional Coastal Ocean Observing Systems (RCOOS). The Gulf of Mexico Coastal Ocean Observing System (GCOOS) is one of eleven RCOOS. This paper describes how GCOOS is progressing as a system of systems to carry out data collection, analysis, product generation, dissemination of information, and data archival. These elements are provided by federal, state, and local government agencies, academic institutions, non-government organization, and the private sector. This end-to-end system supports the seven societal goals of the IOOS, as provided by the U.S. Commission on Ocean Policy: detect and forecast oceanic components of climate variability, facilitate safe and efficient marine operations, ensure national security, manage marine resources, preserve and restore healthy marine ecosystems, mitigate natural hazards, and ensure public health. The initial building blocks for GCOOS include continuing in situ observations, satellite products, models, and other information supported by federal and state government, private industry, and academia. GCOOS has compiled an inventory of such activities, together with descriptions, costs, sources of support, and possible out-year budgets. These activities provide information that will have broader use as they are integrated and enhanced. GCOOS has begun that process by several approaches. First, GCOOS has established a web site (www.gcoos.org) which is a portal to such activities and contains pertinent information

A Bayesian Approach to Evaluating Consistency between Climate Model Output and Observations

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Cressie, N.; Teixeira, J.

2010-12-01

Like other scientific and engineering problems that involve physical modeling of complex systems, climate models can be evaluated and diagnosed by comparing their output to observations of similar quantities. Though the global remote sensing data record is relatively short by climate research standards, these data offer opportunities to evaluate model predictions in new ways. For example, remote sensing data are spatially and temporally dense enough to provide distributional information that goes beyond simple moments to allow quantification of temporal and spatial dependence structures. In this talk, we propose a new method for exploiting these rich data sets using a Bayesian paradigm. For a collection of climate models, we calculate posterior probabilities its members best represent the physical system each seeks to reproduce. The posterior probability is based on the likelihood that a chosen summary statistic, computed from observations, would be obtained when the model's output is considered as a realization from a stochastic process. By exploring how posterior probabilities change with different statistics, we may paint a more quantitative and complete picture of the strengths and weaknesses of the models relative to the observations. We demonstrate our method using model output from the CMIP archive, and observations from NASA's Atmospheric Infrared Sounder.

Mirror neuron system and observational learning: behavioral and neurophysiological evidence.

PubMed

Lago-Rodriguez, Angel; Lopez-Alonso, Virginia; Fernández-del-Olmo, Miguel

2013-07-01

Three experiments were performed to study observational learning using behavioral, perceptual, and neurophysiological data. Experiment 1 investigated whether observing an execution model, during physical practice of a transitive task that only presented one execution strategy, led to performance improvements compared with physical practice alone. Experiment 2 investigated whether performing an observational learning protocol improves subjects' action perception. In experiment 3 we evaluated whether the type of practice performed determined the activation of the Mirror Neuron System during action observation. Results showed that, compared with physical practice, observing an execution model during a task that only showed one execution strategy does not provide behavioral benefits. However, an observational learning protocol allows subjects to predict more precisely the outcome of the learned task. Finally, intersperse observation of an execution model with physical practice results in changes of primary motor cortex activity during the observation of the motor pattern previously practiced, whereas modulations in the connectivity between primary and non primary motor areas (PMv-M1; PPC-M1) were not affected by the practice protocol performed by the observer. Copyright © 2013 Elsevier B.V. All rights reserved.

Jupiter System Observer

NASA Technical Reports Server (NTRS)

Senske, Dave; Kwok, Johnny

2008-01-01

This slide presentation reviews the proposed mission for the Jupiter System Observer. The presentation also includes overviews of the mission timeline, science goals, and spacecraftspecifications for the satellite.

Characterising Hot-Jupiters' atmospheres with observations and modelling

NASA Astrophysics Data System (ADS)

Tinetti, G.

2007-08-01

Exoplanet transit photometry and spectroscopy are currently the best techniques to probe the atmospheres of extrasolar worlds. The best targets to be observed with these methods, are the planets that orbit very close to their parent star, both because their probability to transit grows and their atmospheres are warmer and more expanded, hence easier to probe. These characteristics are met by the so called Hot-Jupiters, massive low-density gaseous planets orbiting very close-in. Phase-curves allow to observe the change in brightness in the combined light of the planet-star system, also for non-transiting exoplanets. We review here the most crucial observations performed with the Hubble and Spitzer Space Telescopes at multiple wavelenghts, and the most successful models proposed in the literature to plan and interpret those observations. In particular we will focus on most recent observations and modelling claiming the detection of water vapour in the atmospheres of these planets. Further into the future, the JamesWebb Space Telescope will allow to probe the atmospheres of smaller size-planets with the same techniques. We briefly report here the results expected for hot and warm Neptunes, or transiting terrestrial planets.

Evaluating the strength of the land$-$atmosphere moisture feedback in Earth system models using satellite observations

DOE PAGES

Levine, Paul A.; Randerson, James T.; Swenson, Sean C.; ...

2016-12-09

The relationship between terrestrial water storage (TWS) and atmospheric processes has important implications for predictability of climatic extremes and projection of future climate change. In places where moisture availability limits evapotranspiration (ET), variability in TWS has the potential to influence surface energy fluxes and atmospheric conditions. Where atmospheric conditions, in turn, influence moisture availability, a full feedback loop exists. Here we developed a novel approach for measuring the strength of both components of this feedback loop, i.e., the forcing of the atmosphere by variability in TWS and the response of TWS to atmospheric variability, using satellite observations of TWS, precipitation,more » solar radiation, and vapor pressure deficit during 2002–2014. Our approach defines metrics to quantify the relationship between TWS anomalies and climate globally on a seasonal to interannual timescale. Metrics derived from the satellite data were used to evaluate the strength of the feedback loop in 38 members of the Community Earth System Model (CESM) Large Ensemble (LENS) and in six models that contributed simulations to phase 5 of the Coupled Model Intercomparison Project (CMIP5). We found that both forcing and response limbs of the feedback loop in LENS were stronger than in the satellite observations in tropical and temperate regions. Feedbacks in the selected CMIP5 models were not as strong as those found in LENS, but were still generally stronger than those estimated from the satellite measurements. Consistent with previous studies conducted across different spatial and temporal scales, our analysis suggests that models may overestimate the strength of the feedbacks between the land surface and the atmosphere. Lastly, we describe several possible mechanisms that may contribute to this bias, and discuss pathways through which models may overestimate ET or overestimate the sensitivity of ET to TWS.« less

Impact of Targeted Ocean Observations for Improving Ocean Model Initialization for Coupled Hurricane Forecasting

NASA Astrophysics Data System (ADS)

Halliwell, G. R.; Srinivasan, A.; Kourafalou, V. H.; Yang, H.; Le Henaff, M.; Atlas, R. M.

2012-12-01

The accuracy of hurricane intensity forecasts produced by coupled forecast models is influenced by errors and biases in SST forecasts produced by the ocean model component and the resulting impact on the enthalpy flux from ocean to atmosphere that powers the storm. Errors and biases in fields used to initialize the ocean model seriously degrade SST forecast accuracy. One strategy for improving ocean model initialization is to design a targeted observing program using airplanes and in-situ devices such as floats and drifters so that assimilation of the additional data substantially reduces errors in the ocean analysis system that provides the initial fields. Given the complexity and expense of obtaining these additional observations, observing system design methods such as OSSEs are attractive for designing efficient observing strategies. A new fraternal-twin ocean OSSE system based on the HYbrid Coordinate Ocean Model (HYCOM) is used to assess the impact of targeted ocean profiles observed by hurricane research aircraft, and also by in-situ float and drifter deployments, on reducing errors in initial ocean fields. A 0.04-degree HYCOM simulation of the Gulf of Mexico is evaluated as the nature run by determining that important ocean circulation features such as the Loop Current and synoptic cyclones and anticyclones are realistically simulated. The data-assimilation system is run on a 0.08-degree HYCOM mesh with substantially different model configuration than the nature run, and it uses a new ENsemble Kalman Filter (ENKF) algorithm optimized for the ocean model's hybrid vertical coordinates. The OSSE system is evaluated and calibrated by first running Observing System Experiments (OSEs) to evaluate existing observing systems, specifically quantifying the impact of assimilating more than one satellite altimeter, and also the impact of assimilating targeted ocean profiles taken by the NOAA WP-3D hurricane research aircraft in the Gulf of Mexico during the Deepwater

Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

NASA Technical Reports Server (NTRS)

Farhadi, Leila; Reichle, Rolf H.; DeLannoy, Gabrielle J. M.; Kimball, John S.

2014-01-01

The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

Foveated model observers to predict human performance in 3D images

NASA Astrophysics Data System (ADS)

Lago, Miguel A.; Abbey, Craig K.; Eckstein, Miguel P.

2017-03-01

We evaluate 3D search requires model observers that take into account the peripheral human visual processing (foveated models) to predict human observer performance. We show that two different 3D tasks, free search and location-known detection, influence the relative human visual detectability of two signals of different sizes in synthetic backgrounds mimicking the noise found in 3D digital breast tomosynthesis. One of the signals resembled a microcalcification (a small and bright sphere), while the other one was designed to look like a mass (a larger Gaussian blob). We evaluated current standard models observers (Hotelling; Channelized Hotelling; non-prewhitening matched filter with eye filter, NPWE; and non-prewhitening matched filter model, NPW) and showed that they incorrectly predict the relative detectability of the two signals in 3D search. We propose a new model observer (3D Foveated Channelized Hotelling Observer) that incorporates the properties of the visual system over a large visual field (fovea and periphery). We show that the foveated model observer can accurately predict the rank order of detectability of the signals in 3D images for each task. Together, these results motivate the use of a new generation of foveated model observers for predicting image quality for search tasks in 3D imaging modalities such as digital breast tomosynthesis or computed tomography.

Observing System Evaluations Using GODAE Systems

DTIC Science & Technology

2009-09-01

DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release, distribution is unlimite 13. SUPPLEMENTARY NOTES 20091228151 14. ABSTRACT Global ocean...forecast systems, developed under the Global Ocean Data Assimilation Experiment (GODAE), are a powerful means of assessing the impact of different...components of the Global Ocean Observing System (GOOS). Using a range of analysis tools and approaches, GODAE systems are useful for quantifying the

Successes and Challenges in Linking Observations and Modeling of Marine and Terrestrial Cryospheric Processes

NASA Astrophysics Data System (ADS)

Herzfeld, U. C.; Hunke, E. C.; Trantow, T.; Greve, R.; McDonald, B.; Wallin, B.

2014-12-01

Understanding of the state of the cryosphere and its relationship to other components of the Earth system requires both models of geophysical processes and observations of geophysical properties and processes, however linking observations and models is far from trivial. This paper looks at examples from sea ice and land ice model-observation linkages to examine some approaches, challenges and solutions. In a sea-ice example, ice deformation is analyzed as a key process that indicates fundamental changes in the Arctic sea ice cover. Simulation results from the Los Alamos Sea-Ice Model CICE, which is also the sea-ice component of the Community Earth System Model (CESM), are compared to parameters indicative of deformation as derived from mathematical analysis of remote sensing data. Data include altimeter, micro-ASAR and image data from manned and unmanned aircraft campaigns (NASA OIB and Characterization of Arctic Sea Ice Experiment, CASIE). The key problem to linking data and model results is the derivation of matching parameters on both the model and observation side.For terrestrial glaciology, we include an example of a surge process in a glacier system and and example of a dynamic ice sheet model for Greenland. To investigate the surge of the Bering Bagley Glacier System, we use numerical forward modeling experiments and, on the data analysis side, a connectionist approach to analyze crevasse provinces. In the Greenland ice sheet example, we look at the influence of ice surface and bed topography, as derived from remote sensing data, on on results from a dynamic ice sheet model.

Study on observation planning of LAMOST focal plane positioning system and its simulation

NASA Astrophysics Data System (ADS)

Zhai, Chao; Jin, Yi; Peng, Xiaobo; Xing, Xiaozheng

2006-06-01

Fiber Positioning System of LAMOST focal plane based on subarea thinking, adopts a parallel controllable positioning plan, the structure is designed as a round area and overlapped each other in order to eliminate the un-observation region. But it also makes the observation efficiency of the system become an important problem. In this paper According to the system, the model of LAMOST focal plane Observation Planning including 4000 fiber positioning units is built, Stars are allocated using netflow algorithm and mechanical collisions are diminished through the retreat algorithm, then the simulation of the system's observation efficiency is carried out. The problem of observation efficiency of LAMOST focal plane is analysed systemic and all-sided from the aspect of overlapped region, fiber positioning units, observation radius, collisions and so on. The observation efficiency of the system in theory is describes and the simulation indicates that the system's observation efficiency is acceptable. The analyses play an indicative role on the design of the LAMOST focal plane structure.

Control of rift asymmetry and segmentation on the thermal architecture of hyperextended rift systems: insights from Pyrenean field observations and numerical modelling

NASA Astrophysics Data System (ADS)

Lescoutre, Rodolphe; Tugend, Julie; Brune, Sascha; Manatschal, Gianreto

2017-04-01

Mid-Cretaceous rift basins are exposed in the Pyrenees providing key information on rifted domain formation that is not available at present-day rift system. Substantial paleotemperature and thermochronological data have been collected and published in numerous recent papers. These data show a strong heterogeneity in the distribution of peak temperatures within the Cretaceous rift basins. Locations that experienced relatively high or low temperatures appear to cluster in specific areas along strike. These areas have been interpreted as either reflecting hot and cold conditions during rifting, or alternatively, a change in the polarity of a strongly asymmetric rift systems. In this study, we test if the observed variability of peak temperatures can be explained by segmentation and a change in polarity of an asymmetrical upper/lower plate rift model. To this aim we restore the observed syn- to early post-rift peak temperatures to their paleo-location within sections across the evolving rift system. In the meantime, we conduct numerical models of rift migration leading to asymmetrical extension that are benchmarked with geological and geophysical observations from the Pyrenees. From the models, we extract thermal information at different stages of rifting that are finally compared to the thermal data from the Pyrenean Cretaceous rift basins. This work employs a novel approach by comparing thermal output from numerical modelling with the distribution of peak temperatures and thermal gradient from field data. As such, these results may have substantial implications to further understand the pre-orogenic thermal evolution of the Pyrenean rift system and the role of segmentation. More generally, the results of this work may unravel the role of rift asymmetry and segmentation on the thermal architecture of hyperextended rift basins and margins.

Using climate models to estimate the quality of global observational data sets.

PubMed

Massonnet, François; Bellprat, Omar; Guemas, Virginie; Doblas-Reyes, Francisco J

2016-10-28

Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection. Copyright © 2016, American Association for the Advancement of Science.

The Earth Observing System

NASA Technical Reports Server (NTRS)

Shaffer, Lisa Robock

1992-01-01

The restructuring of the NASA Earth Observing System (EOS), designed to provide comprehensive long term observations from space of changes occurring on the Earth from natural and human causes in order to have a sound scientific basis for policy decisions on protection of the future, is reported. In response to several factors, the original program approved in the fiscal year 1991 budget was restructured and somewhat reduced in scope. The resulting program uses three different sized launch vehicles to put six different spacecraft in orbit in the first phase, followed by two replacement launches for each of five of the six satellites to maintain a long term observing capability to meet the needs of global climate change research and other science objectives. The EOS system, including the space observatories, the data and information system, and the interdisciplinary global change research effort, are approved and proceeding. Elements of EOS are already in place, such as the research investigations and initial data system capabilities. The flights of precursor satellite and Shuttle missions, the ongoing data analysis, and the evolutionary enhancements to the integrated Earth science data management capabilities are all important building blocks to the full EOS program.

Models of the Jovian Ring and Comparisions With Observations

NASA Astrophysics Data System (ADS)

Juhasz, A.; Horanyi, M.

2008-12-01

A number of in situ and remote sensing observations of the Jovian ring system exist so we can now combine observations from Voyager, Pioneer, Galileo and Cassini, as well as ground based and HST measurements. In this presentation we will compare this large body of observations to available theoretical models of the dust dynamics in the Jovian ring. Common to all models (Burns et al., 1985, 2001 ; Horanyi et al.,1996, 2004) is the basic idea that dust is being continuously produced due to micro-meteoroid bombardment of the moons in this region. Also, the spatial distribution of dust in the halo region inward of the main ring is generally accepted to be a consequence of electrodynamic perturbations acting on small charged dust particles. However, in the suggested theoretical models the time scale for orbital evolution is drastically differ. Burns et al. argues, that in the main ring, dust particles evolve inward very slowly due to Poynting-Robertson drag. A typical micron sized grain is predicted to orbit Jupiter for 104 years before crashing into the atmosphere of Jupiter. Horanyi et al. argues that the radial transport is due to resonant charge variations, dictated by the plasma density distribution. In this model grains are transported on a time scale that is orders of magnitude shorter than predicted by PR drag. Here we use both of these models to generate brightness distributions and predict optical depth distributions for same geometries and wavelengths as that of the observations. Quantitative comparisons of the modeled and the real observations lead us to the conclusion that the dust transport in ring/halo region at Jupiter is mainly due to resonant charge variation.

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

NASA Astrophysics Data System (ADS)

Scholze, Marko; Buchwitz, Michael; Dorigo, Wouter; Guanter, Luis; Quegan, Shaun

2017-07-01

The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

Criticality in conserved dynamical systems: experimental observation vs. exact properties.

PubMed

Marković, Dimitrije; Gros, Claudius; Schuelein, André

2013-03-01

Conserved dynamical systems are generally considered to be critical. We study a class of critical routing models, equivalent to random maps, which can be solved rigorously in the thermodynamic limit. The information flow is conserved for these routing models and governed by cyclic attractors. We consider two classes of information flow, Markovian routing without memory and vertex routing involving a one-step routing memory. Investigating the respective cycle length distributions for complete graphs, we find log corrections to power-law scaling for the mean cycle length, as a function of the number of vertices, and a sub-polynomial growth for the overall number of cycles. When observing experimentally a real-world dynamical system one normally samples stochastically its phase space. The number and the length of the attractors are then weighted by the size of their respective basins of attraction. This situation is equivalent, for theory studies, to "on the fly" generation of the dynamical transition probabilities. For the case of vertex routing models, we find in this case power law scaling for the weighted average length of attractors, for both conserved routing models. These results show that the critical dynamical systems are generically not scale-invariant but may show power-law scaling when sampled stochastically. It is hence important to distinguish between intrinsic properties of a critical dynamical system and its behavior that one would observe when randomly probing its phase space.

Impact of Radiatively Interactive Dust Aerosols on Dust Transport and Mobilization in the NASA Goddard Earth Observing System (GEOS-5) Earth Model

NASA Astrophysics Data System (ADS)

Colarco, P. R.; Rocha Lima, A.; Darmenov, A.; Bloecker, C.

2017-12-01

Mineral dust aerosols scatter and absorb solar and infrared radiation, impacting the energy budget of the Earth system which in turns feeds back on the dynamical processes responsible for mobilization of dust in the first place. In previous work with radiatively interactive aerosols in the NASA Goddard Earth Observing System global model (GEOS-5) we found a positive feedback between dust absorption and emissions. Emissions were the largest for the highest shortwave absorption considered, which additionally produced simulated dust transport in the best agreement with observations. The positive feedback found was in contrast to other modeling studies which instead found a negative feedback, where the impact of dust absorption was to stabilize the surface levels of the atmosphere and so reduce wind speeds. A key difference between our model and other models was that in GEOS-5 we simulated generally larger dust particles, with correspondingly larger infrared absorption that led to a pronounced difference in the diurnal cycle of dust emissions versus simulations where these long wave effects were not considered. In this paper we seek to resolve discrepancies between our previous simulations and those of other modeling groups. We revisit the question of dust radiative feedback on emissions with a recent version of the GEOS-5 system running at a higher spatial resolution and including updates to the parameterizations for dust mobilization, initial dust particle size distribution, loss processes, and radiative transfer, and identify key uncertainties that remain based on dust optical property assumptions.

Autonomous aerial observations to extend and complement the Earth Observing System: a science-driven systems-oriented approach

NASA Astrophysics Data System (ADS)

Sandford, Stephen P.; Harrison, F. W.; Langford, John; Johnson, James W.; Qualls, Garry; Emmitt, David; Jones, W. Linwood; Shugart, Herman H., Jr.

2004-12-01

The current Earth observing capability depends primarily on spacecraft missions and ground-based networks to provide the critical on-going observations necessary for improved understanding of the Earth system. Aircraft missions play an important role in process studies but are limited to relatively short-duration flights. Suborbital observations have contributed to global environmental knowledge by providing in-depth, high-resolution observations that space-based and in-situ systems are challenged to provide; however, the limitations of aerial platforms - e.g., limited observing envelope, restrictions associated with crew safety and high cost of operations have restricted the suborbital program to a supporting role. For over a decade, it has been recognized that autonomous aerial observations could potentially be important. Advances in several technologies now enable autonomous aerial observation systems (AAOS) that can provide fundamentally new observational capability for Earth science and applications and thus lead scientists and engineers to rethink how suborbital assets can best contribute to Earth system science. Properly developed and integrated, these technologies will enable new Earth science and operational mission scenarios with long term persistence, higher-spatial and higher-temporal resolution at lower cost than space or ground based approaches. This paper presents the results of a science driven, systems oriented study of broad Earth science measurement needs. These needs identify aerial mission scenarios that complement and extend the current Earth Observing System. These aerial missions are analogous to space missions in their complexity and potential for providing significant data sets for Earth scientists. Mission classes are identified and presented based on science driven measurement needs in atmospheric, ocean and land studies. Also presented is a nominal concept of operations for an AAOS: an innovative set of suborbital assets that

Susquehanna River Basin Hydrologic Observing System (SRBHOS)

NASA Astrophysics Data System (ADS)

Reed, P. M.; Duffy, C. J.; Dressler, K. A.

2004-12-01

system of observations, will intersect the important landforms, climate zones, ecology, and human activities of the basin. Characterizing how humans and climate impact the sustainability of water resources in the Susquehanna River Basin will require an evolutionary approach, involving coordination of historical information and a phased-design for the new observing system. Detecting change (past and present) requires that the atmosphere, vegetation, geochemistry, and hydrology of the Susquehanna, are all observed coherently from the headwaters to the Chesapeake, from the boundary layer to the water table. The River Basin Adaptive Monitoring and Modeling Plan (RAMP) represents the design strategy to coherently select and assess core monitoring sites as well as new sites targeted for both short-term and long term scientific campaigns. Rich in historical research and infrastructure, SRBHOS will serve as a fundamental resource for the hydrologic science community into the future, while providing a "characteristic" hydrologic node in the national network.

The dynamics of human-water systems: comparing observations and simulations

NASA Astrophysics Data System (ADS)

Di Baldassarre, G.; Ciullo, A.; Castellarin, A.; Viglione, A.

2016-12-01

Real-word data of human-flood interactions are compared to the results of stylized socio-hydrological models. These models build on numerous examples from different parts of the world and consider two main prototypes of floodplain systems. Green systems, whereby societies cope with flood risk via non-structural measures, e.g. resettling out of floodplain areas ("living with floods" approach); and Technological systems, whereby societies cope with flood risk by also via structural measures, e.g. building levees ("fighting floods" approach). The floodplain systems of the Tiber River in Rome and the Ganges-Brahmaputra-Meghna Rivers in Bangladesh systems are used as case studies. The comparison of simulations and observations shows the potential of socio-hydrological models in capturing the dynamics of risk emerging from the interactions and feedbacks between social and hydrological processes, such as learning and forgetting effects. It is then discussed how the proposed approach can contribute to a better understanding of flood risk changes and therefore support the process of disaster risk reduction.

The Revised Pole Model and New Observations of Triton

NASA Astrophysics Data System (ADS)

Zhang, H.-Y.; Shen, K.-X.; Qiao, R.-Ch; Dourneau, G.; Yu, Y.

2015-10-01

We used 3108 Earth-based astrometric observations from the Natural Satellite Data Center (NSDC) over more than 30 years time span from 1975 to 2006 for determining the epoch state vectors of the Neptunes largest satellite Triton. In integrating the perturbation equation, the barycentric frame of Neptune-Triton system is adopted, and in considering the oblateness perturbation due to Neptune, a revised pole model describing the precession of the Neptune's pole is used in our calculation. Moreover, a total of 1095 new observed positions of Triton were collected during 46 nights of observations in 2007, 2008 and 2009. We compared our observations to two ephemerides of Triton and most of the available planetary ephemerides of Neptune.

Designing Observation and Modeling Systems to Inform Decisions and Policies on Freshwater Objectives in New Zealand

NASA Astrophysics Data System (ADS)

Baisden, W. T.; Ellis, T.; Rissman, C.; Moore, C.; Matthews, A.

2016-12-01

Declines in New Zealand's freshwater quality have led to legislation - the 2014 National Policy Statement on Freshwater Management (NPS-FM) - which requires regional governments to set "objectives" and design policies accordingly. In most regions, increases in freshwater contaminants are derived largely from intensifying agriculture and come as nitrogen, phosphorous or sediment, or a combination thereof. Here, the development and application of N and O isotopes as natural tracers for nitrate is examined as a case study, in the context of a wider hierarchy of observations such as N concentrations, flow and broader hydrochemistry used for NPS-FM implementation. The analysis of N and O isotopes in nitrate provides specific information on sources and removal processes that cannot be obtained by other measurements. Yet, despite considerable development of the technical methodology and environment-specific interpretation, application of measurements has faced barriers. Many may be typical of science in a small advanced nation with a population of 4.5 million, but others are unique due to New Zealand's limited rural population base and large diversity in physical geography, as well as a unique economic reliance on highly productive pastoral agricultural systems. Seventeen different regional governments are empowered to regulate in ways consistent with local consultation and democracy within their catchment boundaries, but with limited resources to align highly technical observational data to policies and decisions, as well as supporting models. The resulting gaps in communication and technical capability combine with a diversity of approaches to pose both challenges and opportunities for development and application of hierarchical observation systems. Success appears to lie in ensuring decision frameworks can be `mapped', so that different frameworks can be compared, and the benefits of sophisticated observations understood directly in relation to influence on regional

Microwave and infrared simulations of an intense convective system and comparison with aircraft observations

NASA Technical Reports Server (NTRS)

Prasad, N.; Yeh, Hwa-Young M.; Adler, Robert F.; Tao, Wei-Kuo

1995-01-01

A three-dimensional cloud model, radiative transfer model-based simulation system is tested and validated against the aircraft-based radiance observations of an intense convective system in southeastern Virginia on 29 June 1986 during the Cooperative Huntsville Meteorological Experiment. NASA's ER-2, a high-altitude research aircraft with a complement of radiometers operating at 11-micrometer infrared channel and 18-, 37-, 92-, and 183-GHz microwave channels provided data for this study. The cloud model successfully simulated the cloud system with regard to aircraft- and radar-observed cloud-top heights and diameters and with regard to radar-observed reflectivity structure. For the simulation time found to correspond best with the aircraft- and radar-observed structure, brightness temperatures T(sub b) are simulated and compared with observations for all the microwave frequencies along with the 11-micrometer infrared channel. Radiance calculations at the various frequencies correspond well with the aircraft observations in the areas of deep convection. The clustering of 37-147-GHz T(sub b) observations and the isolation of the 18-GHz values over the convective cores are well simulated by the model. The radiative transfer model, in general, is able to simulate the observations reasonably well from 18 GHz through 174 GHz within all convective areas of the cloud system. When the aircraft-observed 18- and 37-GHz, and 90- and 174-GHz T(sub b) are plotted against each other, the relationships have a gradual difference in the slope due to the differences in the ice particle size in the convective and more stratiform areas of the cloud. The model is able to capture these differences observed by the aircraft. Brightness temperature-rain rate relationships compare reasonably well with the aircraft observations in terms of the slope of the relationship. The model calculations are also extended to select high-frequency channels at 220, 340, and 400 GHz to simulate the

Documentation and Validation of the Goddard Earth Observing System (GEOS) Data Assimilation System, Version 4

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); daSilva, Arlindo; Dee, Dick; Bloom, Stephen; Bosilovich, Michael; Pawson, Steven; Schubert, Siegfried; Wu, Man-Li; Sienkiewicz, Meta; Stajner, Ivanka

2005-01-01

This document describes the structure and validation of a frozen version of the Goddard Earth Observing System Data Assimilation System (GEOS DAS): GEOS-4.0.3. Significant features of GEOS-4 include: version 3 of the Community Climate Model (CCM3) with the addition of a finite volume dynamical core; version two of the Community Land Model (CLM2); the Physical-space Statistical Analysis System (PSAS); and an interactive retrieval system (iRET) for assimilating TOVS radiance data. Upon completion of the GEOS-4 validation in December 2003, GEOS-4 became operational on 15 January 2004. Products from GEOS-4 have been used in supporting field campaigns and for reprocessing several years of data for CERES.

Informing Carbon Dynamics in the Community Land Model with Observations from Across Timescales

NASA Astrophysics Data System (ADS)

Fox, A. M.; Hoar, T. J.

2014-12-01

Correct simulation of carbon dynamics in Earth System Models is required to accurately predict both short and long-term land carbon-cycle climate and concentration feedbacks. As new model structures and parameterizations of increasing complexity are introduced there is an ever present need for data to inform these developments, either indirectly through benchmarking activities, or directly through model-data fusion techniques. Here we briefly describe a very rich source of data that will come from the National Ecological Observatory Network (NEON), a continental-scale facility that will collect freely available biogeochemical and biophysical data from 60 sites representative of a full range of ecosystems across the USA over 30 years. Relevant data at each site include a full suite of micrometeorology measurements, profiles of CO2 and H2O vapor isotopes, soil temperature, moisture and CO2 flux, fine root images, and plot-based NPP, leaf area and litterfall estimates. This is accompanied by Lidar and hyperspectral derived biomass, leaf area and canopy chemistry at < 1m resolution of 100s km2. Critically, these observations are well calibrated and highly standardized across sites allowing comparisons, whilst plot and site selection has been designed to optimize representativeness and spatial scaling opportunities. To illustrate the potential utility of these data in constraining models, we show the range of Community Land Model (CLM) output at NEON site locations, and in model-space look at a number of different functional responses that characterize the model in space and time and could be tested with data. These observations can be used most directly through a data assimilation (DA) system and we demonstrate how we have developed support for CLM within the Data Assimilation Research Testbed (DART) that uses ensemble techniques for state estimation. Using an observing system experiment, we investigate how infrequent observations of carbon stocks constrain model

Observability Analysis of a Matrix Kalman Filter-Based Navigation System Using Visual/Inertial/Magnetic Sensors

PubMed Central

Feng, Guohu; Wu, Wenqi; Wang, Jinling

2012-01-01

A matrix Kalman filter (MKF) has been implemented for an integrated navigation system using visual/inertial/magnetic sensors. The MKF rearranges the original nonlinear process model in a pseudo-linear process model. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system is observable. It has been proved that such observability conditions are: (a) at least one degree of rotational freedom is excited, and (b) at least two linearly independent horizontal lines and one vertical line are observed. Experimental results have validated the correctness of these observability conditions. PMID:23012523

An Observing System Simulation Experiment (OSSE) Investigating the OMI Aerosol Products Using Simulated Aerosol and Atmospheric Fields from the NASA GEOS-5 Model

NASA Astrophysics Data System (ADS)

Colarco, P. R.; Gasso, S.; Jethva, H. T.; Buchard, V.; Ahn, C.; Torres, O.; daSilva, A.

2016-12-01

Output from the NASA Goddard Earth Observing System, version 5 (GEOS-5) Earth system model is used to simulate the top-of-atmosphere 354 and 388 nm radiances observed by the Ozone Monitoring Instrument (OMI) onboard the Aura spacecraft. The principle purpose of developing this simulator tool is to compute from the modeled fields the so-called OMI Aerosol Index (AI), which is a more fundamental retrieval product than higher level products such as the aerosol optical depth (AOD) or absorbing aerosol optical depth (AAOD). This lays the groundwork for eventually developing a capability to assimilate either the OMI AI or its radiances, which would provide further constraint on aerosol loading and absorption properties for global models. We extend the use of the simulator capability to understand the nature of the OMI aerosol retrieval algorithms themselves in an Observing System Simulation Experiment (OSSE). The simulated radiances are used to calculate the AI from the modeled fields. These radiances are also provided to the OMI aerosol algorithms, which return their own retrievals of the AI, AOD, and AAOD. Our assessment reveals that the OMI-retrieved AI can be mostly harmonized with the model-derived AI given the same radiances provided a common surface pressure field is assumed. This is important because the operational OMI algorithms presently assume a fixed pressure field, while the contribution of molecular scattering to the actual OMI signal in fact responds to the actual atmospheric pressure profile, which is accounted for in our OSSE by using GEOS-5 produced atmospheric reanalyses. Other differences between the model and OMI AI are discussed, and we present a preliminary assessment of the OMI AOD and AAOD products with respect to the known inputs from the GEOS-5 simulation.

Observer-Based Discrete-Time Nonnegative Edge Synchronization of Networked Systems.

PubMed

Su, Housheng; Wu, Han; Chen, Xia

2017-10-01

This paper studies the multi-input and multi-output discrete-time nonnegative edge synchronization of networked systems based on neighbors' output information. The communication relationship among the edges of networked systems is modeled by well-known line graph. Two observer-based edge synchronization algorithms are designed, for which some necessary and sufficient synchronization conditions are derived. Moreover, some computable sufficient synchronization conditions are obtained, in which the feedback matrix and the observer matrix are computed by solving the linear programming problems. We finally design several simulation examples to demonstrate the validity of the given nonnegative edge synchronization algorithms.

Multiscale Cloud System Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell W.

2009-01-01

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

Observing Human-induced Linkages between Urbanization and Earth's Climate System

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Jin, Menglin

2004-01-01

Urbanization is one of the extreme cases of land use change. Most of world s population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025, 60% of the world s population will live in cities. Human activity in urban environments also alters atmospheric composition; impacts components of the water cycle; and modifies the carbon cycle and ecosystems. However, our understanding of urbanization on the total Earth-climate system is incomplete. Better understanding of how the Earth s atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of the urban environment on this climate system is critical. The goal of the 2003 AGU Union session Human-induced climate variations on urban areas: From observations to modeling was to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results on observing and modeling components of the urban environment with the intent of sampling our current stand and discussing future direction on this topic. Herein, a summary and discussion of the observations component of the session are presented.

Observer design for compensation of network-induced delays in integrated communication and control systems

NASA Technical Reports Server (NTRS)

Luck, R.; Ray, A.

1988-01-01

A method for compensating the effects of network-induced delays in integrated communication and control systems (ICCS) is proposed, and a finite-dimensional time-invariant ICCS model is developed. The problem of analyzing systems with time-varying and stochastic delays is circumvented by the application of a deterministic observer. For the case of controller-to-actuator delays, the observed design must rely on an extended model which represents the delays as additional states.

Dynamics of rotationally fissioned asteroids: Source of observed small asteroid systems

NASA Astrophysics Data System (ADS)

Jacobson, Seth A.; Scheeres, Daniel J.

2011-07-01

We present a model of near-Earth asteroid (NEA) rotational fission and ensuing dynamics that describes the creation of synchronous binaries and all other observed NEA systems including: doubly synchronous binaries, high- e binaries, ternary systems, and contact binaries. Our model only presupposes the Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect, "rubble pile" asteroid geophysics, and gravitational interactions. The YORP effect torques a "rubble pile" asteroid until the asteroid reaches its fission spin limit and the components enter orbit about each other (Scheeres, D.J. [2007]. Icarus 189, 370-385). Non-spherical gravitational potentials couple the spin states to the orbit state and chaotically drive the system towards the observed asteroid classes along two evolutionary tracks primarily distinguished by mass ratio. Related to this is a new binary process termed secondary fission - the secondary asteroid of the binary system is rotationally accelerated via gravitational torques until it fissions, thus creating a chaotic ternary system. The initially chaotic binary can be stabilized to create a synchronous binary by components of the fissioned secondary asteroid impacting the primary asteroid, solar gravitational perturbations, and mutual body tides. These results emphasize the importance of the initial component size distribution and configuration within the parent asteroid. NEAs may go through multiple binary cycles and many YORP-induced rotational fissions during their approximately 10 Myr lifetime in the inner Solar System. Rotational fission and the ensuing dynamics are responsible for all NEA systems including the most commonly observed synchronous binaries.

Incorporating a Full-Physics Meteorological Model into an Applied Atmospheric Dispersion Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berg, Larry K.; Allwine, K Jerry; Rutz, Frederick C.

2004-08-23

A new modeling system has been developed to provide a non-meteorologist with tools to predict air pollution transport in regions of complex terrain. This system couples the Penn State/NCAR Mesoscale Model 5 (MM5) with Earth Tech’s CALMET-CALPUFF system using a unique Graphical User Interface (GUI) developed at Pacific Northwest National Laboratory. This system is most useful in data-sparse regions, where there are limited observations to initialize the CALMET model. The user is able to define the domain of interest, provide details about the source term, and enter a surface weather observation through the GUI. The system then generates initial conditionsmore » and time constant boundary conditions for use by MM5. MM5 is run and the results are piped to CALPUFF for the dispersion calculations. Contour plots of pollutant concentration are prepared for the user. The primary advantages of the system are the streamlined application of MM5 and CALMET, limited data requirements, and the ability to run the coupled system on a desktop or laptop computer. In comparison with data collected as part of a field campaign, the new modeling system shows promise that a full-physics mesoscale model can be used in an applied modeling system to effectively simulate locally thermally-driven winds with minimal observations as input. An unexpected outcome of this research was how well CALMET represented the locally thermally-driven flows.« less

Objectively Optimized Observation Direction System Providing Situational Awareness for a Sensor Web

NASA Astrophysics Data System (ADS)

Aulov, O.; Lary, D. J.

2010-12-01

There is great utility in having a flexible and automated objective observation direction system for the decadal survey missions and beyond. Such a system allows us to optimize the observations made by suite of sensors to address specific goals from long term monitoring to rapid response. We have developed such a prototype using a network of communicating software elements to control a heterogeneous network of sensor systems, which can have multiple modes and flexible viewing geometries. Our system makes sensor systems intelligent and situationally aware. Together they form a sensor web of multiple sensors working together and capable of automated target selection, i.e. the sensors “know” where they are, what they are able to observe, what targets and with what priorities they should observe. This system is implemented in three components. The first component is a Sensor Web simulator. The Sensor Web simulator describes the capabilities and locations of each sensor as a function of time, whether they are orbital, sub-orbital, or ground based. The simulator has been implemented using AGIs Satellite Tool Kit (STK). STK makes it easy to analyze and visualize optimal solutions for complex space scenarios, and perform complex analysis of land, sea, air, space assets, and shares results in one integrated solution. The second component is target scheduler that was implemented with STK Scheduler. STK Scheduler is powered by a scheduling engine that finds better solutions in a shorter amount of time than traditional heuristic algorithms. The global search algorithm within this engine is based on neural network technology that is capable of finding solutions to larger and more complex problems and maximizing the value of limited resources. The third component is a modeling and data assimilation system. It provides situational awareness by supplying the time evolution of uncertainty and information content metrics that are used to tell us what we need to observe and the

Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tao, Wei-Kuo; Houze, Robert, A., Jr.; Zeng, Xiping

This three-year project, in cooperation with Professor Bob Houze at University of Washington, has been successfully finished as planned. Both ARM (the Atmospheric Radiation Measurement Program) data and cloud-resolving model (CRM) simulations were used to identify the water budgets of clouds observed in two international field campaigns. The research results achieved shed light on several key processes of clouds in climate change (or general circulation models), which are summarized below. 1. Revealed the effect of mineral dust on mesoscale convective systems (MCSs) Two international field campaigns near a desert and a tropical coast provided unique data to drive and evaluatemore » CRM simulations, which are TWP-ICE (the Tropical Warm Pool International Cloud Experiment) and AMMA (the African Monsoon Multidisciplinary Analysis). Studies of the two campaign data were contrasted, revealing that much mineral dust can bring about large MCSs via ice nucleation and clouds. This result was reported as a PI presentation in the 3rd ASR Science Team meeting held in Arlington, Virginia in March 2012. A paper on the studies was published in the Journal of the Atmospheric Sciences (Zeng et al. 2013). 2. Identified the effect of convective downdrafts on ice crystal concentration Using the large-scale forcing data from TWP-ICE, ARM-SGP (the Southern Great Plains) and other field campaigns, Goddard CRM simulations were carried out in comparison with radar and satellite observations. The comparison between model and observations revealed that convective downdrafts could increase ice crystal concentration by up to three or four orders, which is a key to quantitatively represent the indirect effects of ice nuclei, a kind of aerosol, on clouds and radiation in the Tropics. This result was published in the Journal of the Atmospheric Sciences (Zeng et al. 2011) and summarized in the DOE/ASR Research Highlights Summaries (see http://www.arm.gov/science/highlights/RMjY5/view). 3. Used

The Livingstone Model of a Main Propulsion System

NASA Technical Reports Server (NTRS)

Bajwa, Anupa; Sweet, Adam; Korsmeyer, David (Technical Monitor)

2003-01-01

Livingstone is a discrete, propositional logic-based inference engine that has been used for diagnosis of physical systems. We present a component-based model of a Main Propulsion System (MPS) and say how it is used with Livingstone (L2) in order to implement a diagnostic system for integrated vehicle health management (IVHM) for the Propulsion IVHM Technology Experiment (PITEX). We start by discussing the process of conceptualizing such a model. We describe graphical tools that facilitated the generation of the model. The model is composed of components (which map onto physical components), connections between components and constraints. A component is specified by variables, with a set of discrete, qualitative values for each variable in its local nominal and failure modes. For each mode, the model specifies the component's behavior and transitions. We describe the MPS components' nominal and fault modes and associated Livingstone variables and data structures. Given this model, and observed external commands and observations from the system, Livingstone tracks the state of the MPS over discrete time-steps by choosing trajectories that are consistent with observations. We briefly discuss how the compiled model fits into the overall PITEX architecture. Finally we summarize our modeling experience, discuss advantages and disadvantages of our approach, and suggest enhancements to the modeling process.

The Southern California Coastal Ocean Observing System (SCCOOS): Developing A Coastal Observation System To Enable Both Science Based Decision Making And Scientific Discovery

NASA Astrophysics Data System (ADS)

Terrill, E.; John, O.

2005-05-01

The Southern California Coastal Ocean Observing System (SCCOOS) is a consortium that extends from Northern Baja CA in Mexico to Morro Bay at the southern edge of central California, and aims to streamline, coordinate, and further develop individual institutional efforts by creating an integrated, multidisciplinary coastal observatory in the Bight of Southern California for the benefit of society. By leveraging existing infrastructure, partnerships, and private, local, state, and federal resources, SCCOOS is developing a fully operational coastal observation system to address issues related to coastal water quality, marine life resources, and coastal hazards for end user communities spanning local, state, and federal interests. However, to establish a sensible observational approach to address these societal drivers, sound scientific approaches are required in both the system design and the transformation of data to useful products. Since IOOS and coastal components of the NSF Ocean Observatories Initiative (OOI) are not mutually exclusive within this framework, the SCCOOS consortium of observatory implementers have created an organizational structure that encourages dovetailing of OOI into the routine observations provided by the operational components of a regional IOOS. To begin the development, SCCOOS has grant funding from the California Coastal Conservancy as part of a $21M, statewide initiative to establish a Coastal Ocean Currents Monitoring Program, and funding from NOAA's Coastal Observing Technology System (COTS). In addition, SCCOOS is leveraging IT development that has been supported by the NSF Information Technology Research program Real-time observatories, Applications,and Data Manageemnt Network (ROADNET), and anticipates using developments which will result from the NSF Laboratory for Ocean Observatory Knowledge Integration Grid (LOOKING) program. The observational components now funded at SCCOOS include surface current mapping by HF radar; high

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

NASA Technical Reports Server (NTRS)

Shie, C.-L.; Tao, W.-K.; Hou, A.; Lin, X.

2006-01-01

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to

Towards a Tropical Pacific Observing System for 2020 and Beyond.

NASA Astrophysics Data System (ADS)

Hill, K. L.; Kessler, W. S.; Smith, N.

2016-02-01

The international TPOS 2020 Project arose out of a review workshop in January 2014, following challenges sustaining TAO-TRITON array in 2012, with the aim of rethinking the tropical Pacific arrays in light of new scientific understanding and new ocean technology since its original design in the 1980s-90s. Observing and understanding ENSO remains a fundamental motivation, extending to biogeochemical phenomena, to processes on smaller scales that rectify into the low frequency, and, to the interaction of the coupled boundary layers of the upper ocean and lower atmosphere. Our primary customers remain the operational prediction centers and we will design an array to support research into physical processes, especially those not well represented in current-generation models. Current-generation forecast systems (data assimilation and the model physics) do not make effective-enough use of observations, thus the modeling centers are well-represented in the TPOS 2020 structure and our sampling is targeted to where the forecasts systems need guidance for improvement While we advocate evolution of the present arrays, the long climate records built up at mooring sites, repeated ship surveys, and island stations are fundamental to detecting and diagnosing both natural climate variability and detecting climate change signatures. Task teams have been established in specific topic areas. These will report in mid-2016, when a plan for the revised arrays will be presented to the agencies and governments, for completion of the evolution by 2020.This presentation will discuss the motivation, guiding principles, and potential changes of direction for the tropical Pacific observing system.

Observing Natural Hazards: Tsunami, Hurricane, and El Niño Observations from the NDBC Ocean Observing System of Systems

NASA Astrophysics Data System (ADS)

O'Neil, K.; Bouchard, R.; Burnett, W. H.; Aldrich, C.

2009-12-01

The National Oceanic and Atmospheric Administration’s (NOAA) National Data Buoy Center (NDBC) operates and maintains the NDBC Ocean Observing Systems of Systems (NOOSS), comprised of 3 networks that provide critical information before and during and after extreme hazards events, such as tsunamis, hurricanes, and El Niños. While each system has its own mission, they have in common the requirement to remain on station in remote areas of the ocean to provide reliable and accurate observations. After the 2004 Sumatran Tsunami, NOAA expanded its network of tsunameters from six in the Pacific Ocean to a vast network of 39 stations providing information to Tsunami Warning Centers to enable faster and more accurate tsunami warnings for coastal communities in the Pacific, Atlantic, Caribbean and the Gulf of Mexico. The tsunameter measurements are used to detect the amplitude and period of the tsunamis, and the data can be assimilated into models for the prediction and impact of the tsunamis to coastal communities. The network has been used for the detection of tsunamis generated by earthquakes, including the 2006 and 2007 Kuril Islands, 2007 Peru, and Solomon Islands, and most recently for the 2009 Dusky Sound, New Zealand earthquake. In August 2009, the NOAA adjusted its 2009 Atlantic Hurricane Seasonal Outlooks from above normal to near or below normal activity, primarily due to a strengthening El Niño. A key component in the detection of that El Niño was the Tropical Atmosphere Ocean Array (TAO) operated by NDBC. TAO provides real-time data for improved detection, understanding, and prediction of El Niño and La Niña. The 55-buoy TAO array spans the central and eastern equatorial Pacific providing real-time and post-deployment recovery data to support climate analysis and forecasts. Although, in this case, the El Niño benefits the tropical Atlantic, the alternate manifestation, La Niña typically enhances hurricane activity in the Atlantic. The various phases of

Operable Data Management for Ocean Observing Systems

NASA Astrophysics Data System (ADS)

Chavez, F. P.; Graybeal, J. B.; Godin, M. A.

2004-12-01

As oceanographic observing systems become more numerous and complex, data management solutions must follow. Most existing oceanographic data management systems fall into one of three categories: they have been developed as dedicated solutions, with limited application to other observing systems; they expect that data will be pre-processed into well-defined formats, such as netCDF; or they are conceived as robust, generic data management solutions, with complexity (high) and maturity and adoption rates (low) to match. Each approach has strengths and weaknesses; no approach yet fully addresses, nor takes advantage of, the sophistication of ocean observing systems as they are now conceived. In this presentation we describe critical data management requirements for advanced ocean observing systems, of the type envisioned by ORION and IOOS. By defining common requirements -- functional, qualitative, and programmatic -- for all such ocean observing systems, the performance and nature of the general data management solution can be characterized. Issues such as scalability, maintaining metadata relationships, data access security, visualization, and operational flexibility suggest baseline architectural characteristics, which may in turn lead to reusable components and approaches. Interoperability with other data management systems, with standards-based solutions in metadata specification and data transport protocols, and with the data management infrastructure envisioned by IOOS and ORION, can also be used to define necessary capabilities. Finally, some requirements for the software infrastructure of ocean observing systems can be inferred. Early operational results and lessons learned, from development and operations of MBARI ocean observing systems, are used to illustrate key requirements, choices, and challenges. Reference systems include the Monterey Ocean Observing System (MOOS), its component software systems (Software Infrastructure and Applications for MOOS, and

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

2014-01-01

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

Constraining Cosmological Models with Different Observations

NASA Astrophysics Data System (ADS)

Wei, J. J.

2016-07-01

cosmological probes, perhaps even out to redshifts much greater (z≫2) than those accessible using SNe Ia. However, the currently available sample of SNe Ia is still quite small. Our simulations have shown that if SLSNe Ic can be commonly detected in the future, they have the potential of greatly refining the measurement of cosmological parameters, particularly the parameter w_{de} of the dark energy equation of state. In Chapter 3, we focus on GRB cosmology. We firstly use GRBs as standard candles in constructing the Hubble diagram at redshifts beyond the current reach of SNe Ia observations. Then we measure high-z star formation rate (SFR) using GRBs. We confirm that the latest Swift sample of GRBs reveals an increasing evolution in the GRB rate relative to SFR at high redshifts. The observed discrepancy between the GRB rate and the SFR may be eliminated by assuming a cosmic evolution in metallicity. Assuming that the SFR and GRB rate are related via an evolving metallicity, we find that the GRB data constrain the slope of the high-z SFR to be -2.41_{-2.09}^{+1.87}. In addition, first stars can only form in structures that are suitably dense, which can be parameterized by the minimum dark matter halo mass M_{min}. M_{min} must play an important role in star formation. We can constrain M_{min}<10^{12.5} M_{⊙} at 68% confidence level from the GRB data. In Chapter 4, we assemble a catalog of 69 strong gravitational lensing systems, and carefully introduce how to constrain cosmological parameters using these important data. We find that both ΛCDM and the R_{h}=ct Universe account for the lens observations quite well, though the precision of these measurements does not appear to be good enough to favor one model over the other. In Chapters 5 and 6, we use measurements of the galaxy-cluster angular diameter distances and 32 age measurements of passively evolving galaxies to test and compare the standard model (ΛCDM) and the R_{h}=ct Universe, respectively. We show that both

Observing system simulation experiments with multiple methods

NASA Astrophysics Data System (ADS)

Ishibashi, Toshiyuki

2014-11-01

An observing System Simulation Experiment (OSSE) is a method to evaluate impacts of hypothetical observing systems on analysis and forecast accuracy in numerical weather prediction (NWP) systems. Since OSSE requires simulations of hypothetical observations, uncertainty of OSSE results is generally larger than that of observing system experiments (OSEs). To reduce such uncertainty, OSSEs for existing observing systems are often carried out as calibration of the OSSE system. The purpose of this study is to achieve reliable OSSE results based on results of OSSEs with multiple methods. There are three types of OSSE methods. The first one is the sensitivity observing system experiment (SOSE) based OSSE (SOSEOSSE). The second one is the ensemble of data assimilation cycles (ENDA) based OSSE (ENDA-OSSE). The third one is the nature-run (NR) based OSSE (NR-OSSE). These three OSSE methods have very different properties. The NROSSE evaluates hypothetical observations in a virtual (hypothetical) world, NR. The ENDA-OSSE is very simple method but has a sampling error problem due to a small size ensemble. The SOSE-OSSE requires a very highly accurate analysis field as a pseudo truth of the real atmosphere. We construct these three types of OSSE methods in the Japan meteorological Agency (JMA) global 4D-Var experimental system. In the conference, we will present initial results of these OSSE systems and their comparisons.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

IEOOS: the Spanish Institute of Oceanography Observing System

NASA Astrophysics Data System (ADS)

Tel, E.; Balbin, R.; Cabanas, J. M.; Garcia, M. J.; Garcia-Martinez, M. C.; Gonzalez-Pola, C.; Lavin, A.; Lopez-Jurado, J. L.; Rodriguez, C.; Ruiz-Villarreal, M.; Sanchez-Leal, R. F.; Vargas-Yanez, M.; Velez-Belchi, P.

2015-10-01

Since its foundation, 100 years ago, the Spanish Institute of Oceanography (IEO) has been observing and measuring the ocean characteristics. Here is a summary of the initiatives of the IEO in the field of the operational oceanography (OO). Some systems like the tide gauges network has been working for more than 70 years. The IEO standard sections began at different moments depending on the local projects, and nowadays there are more than 180 coastal stations and deep-sea ones that are systematically sampled, obtaining physical and biochemical measurements. At this moment, the IEO Observing System (IEOOS) includes 6 permanent moorings equipped with currentmeters, an open-sea ocean-meteorological buoy offshore Santander and an SST satellital image reception station. It also supports the Spanish contribution to the ARGO international program with 47 deployed profilers, and continuous monitoring thermosalinometers, meteorological stations and ADCP onboard the IEO research vessels. The system is completed with the IEO contribution to the RAIA and Gibraltar observatories, and the development of regional prediction models. All these systematic measurements allow the IEO to give responses to ocean research activities, official agencies requirements and industrial and main society demands as navigation, resource management, risks management, recreation, etc, as well as for management development pollution-related economic activities or marine ecosystems. All these networks are linked to international initiatives, framed largely in supranational programs Earth observation sponsored by the United Nations or the European Union. The synchronic observation system permits following spatio-temporal description of some events, as new deep water formation in the Mediterranean Sea and the injection of heat to intermediate waters in the Bay of Biscay after some colder northern storms in winter 2005.

Task Equivalence for Model and Human-Observer Comparisons in SPECT Localization Studies

NASA Astrophysics Data System (ADS)

Sen, Anando; Kalantari, Faraz; Gifford, Howard C.

2016-06-01

While mathematical model observers are intended for efficient assessment of medical imaging systems, their findings should be relevant for human observers as the primary clinical end users. We have investigated whether pursuing equivalence between the model and human-observer tasks can help ensure this goal. A localization receiver operating characteristic (LROC) study tested prostate lesion detection in simulated In-111 SPECT imaging with anthropomorphic phantoms. The test images were 2D slices extracted from reconstructed volumes. The iterative ordered sets expectation-maximization (OSEM) reconstruction algorithm was used with Gaussian postsmoothing. Variations in the number of iterations and the level of postfiltering defined the test strategies in the study. Human-observer performance was compared with that of a visual-search (VS) observer, a scanning channelized Hotelling observer, and a scanning channelized nonprewhitening (CNPW) observer. These model observers were applied with precise information about the target regions of interest (ROIs). ROI knowledge was a study variable for the human observers. In one study format, the humans read the SPECT image alone. With a dual-modality format, the SPECT image was presented alongside an anatomical image slice extracted from the density map of the phantom. Performance was scored by area under the LROC curve. The human observers performed significantly better with the dual-modality format, and correlation with the model observers was also improved. Given the human-observer data from the SPECT study format, the Pearson correlation coefficients for the model observers were 0.58 (VS), -0.12 (CH), and -0.23 (CNPW). The respective coefficients based on the human-observer data from the dual-modality study were 0.72, 0.27, and -0.11. These results point towards the continued development of the VS observer for enhancing task equivalence in model-observer studies.

The Representation of Tropical Cyclones Within the Global William Putman Non-Hydrostatic Goddard Earth Observing System Model (GEOS-5) at Cloud-Permitting Resolutions

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

The Goddard Earth Observing System Model (GEOS-S), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-S from irs standard 72-level 27-km resolution (approx.5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (approx. 3.6 billion cells).

INTAROS: Development of an integrated Arctic observation system under Horizon 2020

NASA Astrophysics Data System (ADS)

Beszczynska-Möller, Agnieszka; Sandven, Stein; Sagen, Hanne

2017-04-01

INTAROS is a research and innovation action funded under the H2020-BG-09 call for the five-year period 2016-2021. INTAROS will develop an integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. INTAROS will have a strong multidisciplinary focus, with tools for integration of data from atmosphere, ocean, cryosphere and terrestrial sciences, provided by institutions in Europe, North America and Asia. Satellite earth observation (EO) data plays an increasingly important role in such observing systems, because the amount of EO data for observing the global climate and environment grows year by year. EO data will therefore be integrated into iAOS based on existing products and databases. In situ observing systems are much more limited due to logistical constraints and cost limitations. The sparseness of in situ data is therefore the largest gap in the overall observing system. INTAROS will assess strengths and weaknesses of existing Arctic observing systems and contribute with innovative solutions to fill some of the critical gaps in the selected networks. INTAROS will develop a platform, iAOS, to search for and access data from distributed databases. The evolution into a sustainable Arctic observing system requires coordination, mobilization and cooperation between the existing European and international infrastructures (in-situ and remote, including space-based), the modeling communities and relevant stakeholder groups. INTAROS will include development of community-based observing systems, where local knowledge is merged with scientific data. Multidisciplinary data integrated under INTAROS will contribute to better understanding of interactions and coupling in the complex Arctic ice-ocean-land-atmosphere system. An integrated Arctic Observation System will enable better-informed decisions and better-documented processes within key sectors (e.g. local communities, shipping, tourism

Operative planning of functional sessions for multisatellite observation and communication systems

NASA Astrophysics Data System (ADS)

Darnopykh, Valeriy V.; Malyshev, Veniamin V.

2012-04-01

An important control aspect of modern satellite observation and communication systems is the control of the functional processes. Functional sessions proceed under conditions of restricted technical ability, large amounts or information to be processed by the on-board equipment, practice inequality of the received information, intentions of system management and operators, interests of customers and other factors. A large number of spacecrafts (SC) in orbital constellation is one of the most important factors affecting the functional process also. Besides that some modern projects of satellite systems are multifunctional that is mixed operations of observation and communication. Therefore the functioning of SC on-board equipment must be accurately co-ordinate. That is why the problem of operative planning the functioning of these systems, while directly affecting the efficiency of the system, is very complex and actual at present. A methodical approach and software package for operative planning of functional processes for satellite observation and communication systems, including multifunctional projects, are considered in the paper. The base scheme of this approach consists of four main stages: stage 1—modeling of SC orbital kinematics and dynamics; stage 2—modeling of system functional processes with all kind of restrictions and criterion function values; stage 3—solving an optimization tasks by numerical applicable algorithms and constructing the optimal (or accuracy) plans; stage 4—repeated plan optimization (different variants) and analyzing. Such scheme is the result of authors practical research which have been realized during last 15 years by the operative planning as for any kinds of single SC as for satellite systems with different structure of orbital constellation. The research helps to unify the procedure of operative planning, to formulate basic principles and approaches for its solving, to develop special software package. The main aspects

El Nino and the Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Halpern, David

1999-01-01

Until a decade ago, an often-quoted expression in oceanography is that very few observations are recorded throughout the ocean. Now, the sentiment is no longer valid in the uppermost 10% of the tropical Pacific Ocean nor at the surface of the global ocean. One of the remarkable legacies of the 1985-1994 Tropical Oceans Global Atmosphere (TOGA) Program is an in situ marine meteorological and upper oceanographic measurement array throughout the equatorial Pacific to monitor the development and maintenance of El Nino episodes. The TOGA Observing System, which initially consisted of moored- and drifting-buoy arrays, a network of commercial ships, and coastal and island stations, now includes a constellation of satellites and data-assimilating models to simulate subsurface oceanographic conditions. The El Nino and La Nina tropical Pacific Ocean observing system represents the initial phase of an integrated global ocean observing system. Remarkable improvements have been made in ocean model simulation of subsurface currents, but some problems persist. For example, the simulation of the South Equatorial Current (SEC) remains an important challenge in the 2S-2N Pacific equatorial wave guide. During El Nino the SEC at the equator is reduced and sometimes the direction is reversed, becoming eastward. Both conditions allow warm water stored in the western Pacific to invade the eastern region, creating an El Nino episode. Assimilation of data is a tenet of faith to correct simulation errors caused by deficiencies in surface fluxes (especially wind stress) and parameterizations of subgrid-scale physical processes. In the first of two numerical experiments, the Pacific SEC was simulated with and without assimilation of subsurface temperature data. Along the equator, a very weak SEC occurred throughout the eastern Pacific, independent of assimilation of data. However, as displayed in the diagram, in the western Pacific there was no satisfactory agreement between the two

Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system

NASA Astrophysics Data System (ADS)

Ciais, P.; Dolman, A. J.; Bombelli, A.; Duren, R.; Peregon, A.; Rayner, P. J.; Miller, C.; Gobron, N.; Kinderman, G.; Marland, G.; Gruber, N.; Chevallier, F.; Andres, R. J.; Balsamo, G.; Bopp, L.; Bréon, F.-M.; Broquet, G.; Dargaville, R.; Battin, T. J.; Borges, A.; Bovensmann, H.; Buchwitz, M.; Butler, J.; Canadell, J. G.; Cook, R. B.; DeFries, R.; Engelen, R.; Gurney, K. R.; Heinze, C.; Heimann, M.; Held, A.; Henry, M.; Law, B.; Luyssaert, S.; Miller, J.; Moriyama, T.; Moulin, C.; Myneni, R. B.; Nussli, C.; Obersteiner, M.; Ojima, D.; Pan, Y.; Paris, J.-D.; Piao, S. L.; Poulter, B.; Plummer, S.; Quegan, S.; Raymond, P.; Reichstein, M.; Rivier, L.; Sabine, C.; Schimel, D.; Tarasova, O.; Valentini, R.; Wang, R.; van der Werf, G.; Wickland, D.; Williams, M.; Zehner, C.

2014-07-01

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher

Toward an integrated Volcanic Ash Observing System in Europe

NASA Astrophysics Data System (ADS)

Lee, Deborah; Lisk, Ian

2014-05-01

Volcanic ash from the Icelandic eruption of Eyjafjallajökull in April and May of 2010 resulted in the decision by many northern European countries to impose significant restrictions on the use of their airspace. The eruption, extent and persistence of the ash revealed how reliant society now is on a safe and efficient air transport system and the fragility of that system when affected by the impact of complex natural hazards. As part of an EC framework programme, the 2011-2013 WEZARD (WEather HaZARD for aeronautics) consortium conducted a cross-industry volcanic ash capability and gap analyses, with the EUMETNET (network of 29 National Meteorological Services) led Work Package 3 focussing on a review of observational and monitoring capabilities, atmospheric dispersion modelling and data exchange. The review has revealed a patchwork of independent observing capabilities for volcanic ash, with some countries investing and others not at all, and most existing networks focus on space-based products. Existing capabilities do not provide the necessary detail on the geographical and vertical extent of volcanic ash and associated levels of contamination, which decision makers in the aviation industry require in order to decide where it is safe to fly. A resultant high priority was identified by WEZARD Work Package 3 for an enhanced observational network of complementary monitoring systems needed to initialise, validate and verify volcanic ash dispersion model output and forecasts. Thus a key recommendation is to invest in a major pre-operational demonstrator "European volcanic ash observing network", focussing on distal monitoring, and aiming to a) fill R&D gaps identified in instrumentation and algorithms and b) integrate data, where possible in near-real-time, from a range of ground-based, airborne and space-based techniques. Here we present a key WEZARD recommendation toward an integrated volcanic ash observing system in Europe, in context with other related projects

SCHeMA web-based observation data information system

NASA Astrophysics Data System (ADS)

Novellino, Antonio; Benedetti, Giacomo; D'Angelo, Paolo; Confalonieri, Fabio; Massa, Francesco; Povero, Paolo; Tercier-Waeber, Marie-Louise

2016-04-01

It is well recognized that the need of sharing ocean data among non-specialized users is constantly increasing. Initiatives that are built upon international standards will contribute to simplify data processing and dissemination, improve user-accessibility also through web browsers, facilitate the sharing of information across the integrated network of ocean observing systems; and ultimately provide a better understanding of the ocean functioning. The SCHeMA (Integrated in Situ Chemical MApping probe) Project is developing an open and modular sensing solution for autonomous in situ high resolution mapping of a wide range of anthropogenic and natural chemical compounds coupled to master bio-physicochemical parameters (www.schema-ocean.eu). The SCHeMA web system is designed to ensure user-friendly data discovery, access and download as well as interoperability with other projects through a dedicated interface that implements the Global Earth Observation System of Systems - Common Infrastructure (GCI) recommendations and the international Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE) standards. This approach will insure data accessibility in compliance with major European Directives and recommendations. Being modular, the system allows the plug-and-play of commercially available probes as well as new sensor probess under development within the project. The access to the network of monitoring probes is provided via a web-based system interface that, being implemented as a SOS (Sensor Observation Service), is providing standard interoperability and access tosensor observations systems through O&M standard - as well as sensor descriptions - encoded in Sensor Model Language (SensorML). The use of common vocabularies in all metadatabases and data formats, to describe data in an already harmonized and common standard is a prerequisite towards consistency and interoperability. Therefore, the SCHeMA SOS has adopted the SeaVox common vocabularies populated by

Nonlinear observer designs for fuel cell power systems

NASA Astrophysics Data System (ADS)

Gorgun, Haluk

A fuel cell is an electrochemical device that combines hydrogen and oxygen, with the aid of electro-catalysts, to produce electricity. A fuel cell consists of a negatively charged anode, a positively charged cathode and an electrolyte, which transports protons or ions. A low temperature fuel cell has an electrical potential of about 0.7 Volt when generating a current density of 300--500 mA/cm2. Practical fuel cell power systems will require a combination of several cells in series (a stack) to satisfy the voltage requirements of specific applications. Fuel cells are suitable for a potentially wide variety of applications, from stationary power generation in the range of hundreds of megawatts to portable electronics in the range of a couple of watts. Efficient operation of a fuel cell system requires advanced feedback control designs. Reliable measurements from the system are necessary to implement such designs. However, most of the commercially available sensors do not operate properly in the reformate and humidified gas streams in fuel cell systems. Sensors working varying degrees of success are too big and costly, and sensors that are potentially low cost are not reliable or do not have the required life time [28]. Observer designs would eliminate sensor needs for measurements, and make feedback control implementable. Since the fuel cell system dynamics are highly nonlinear, observer design is not an easy task. In this study we aim to develop nonlinear observer design methods applicable to fuel cell systems. In part I of the thesis we design an observer to estimate the hydrogen partial pressure in the anode channel. We treat inlet partial pressure as an unknown slowly varying parameter and develop an adaptive observer that employs a nonlinear voltage injection term. However in this design Fuel Processing System (FPS) dynamics are not modelled, and their effect on the anode dynamics are treated as plant uncertainty. In part II of the thesis we study the FPS

Objective analysis of observational data from the FGGE observing systems

NASA Technical Reports Server (NTRS)

Baker, W.; Edelmann, D.; Iredell, M.; Han, D.; Jakkempudi, S.

1981-01-01

An objective analysis procedure for updating the GLAS second and fourth order general atmospheric circulation models using observational data from the first GARP global experiment is described. The objective analysis procedure is based on a successive corrections method and the model is updated in a data assimilation cycle. Preparation of the observational data for analysis and the objective analysis scheme are described. The organization of the program and description of the required data sets are presented. The program logic and detailed descriptions of each subroutine are given.

Benchmarking carbon-nitrogen interactions in Earth System Models to observations: An inter-comparison of nitrogen limitation in global land surface models with carbon and nitrogen cycles (CLM-CN and O-CN)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.

2011-12-01

Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.

Anisotropy in the lowermost mantle beneath the circum-Pacific: observations and modelling

NASA Astrophysics Data System (ADS)

Walpole, J.; Wookey, J. M.; Nowacki, A.; Walker, A.; Kendall, J. M.; Masters, G.; Forte, A. M.

2014-12-01

The lowermost 300 km of mantle (D'') acts as the lower boundary layer to mantle convection. Numerous observations find that this layer is anisotropic, unlike the bulk of the lower mantle above, which is isotropic. The causal mechanism for this anisotropy remains elusive, though its organisation is likely to be imposed by deformation associated with mantle convection. The subduction of the Tethys ocean (since 180 Ma) is predicted to have deposited slab material in D'' in circum-Pacific regions, making these regions cold, encouraging the phase transformation in the MgSiO3 polymorph bridgmanite to a post-perovskite (ppv) structure. These regions are probably rich in ppv. Here we present new observations of anisotropy from shear wave splitting of ScS phases recorded in the epicentral distance range 50-85 degrees. These observations are corrected for anisotropy in the upper mantle beneath source and receiver. Due to the layout of events and receivers we primarily sample D'' beneath the landward side of the circum-Pacific. A detailed pattern of anisotropy is revealed. Anisotropy predominantly leads to SH fast wave propagation with an inferred average strength of 0.9%. This is consistent with many previous observations. However, we do not limit our observations to the SH/SV system. Many observations show non SH/SV fast polarisation. We interpret these data for tilted transverse isotropy (TTI) style anisotropy. We resolve non-radial anisotropy at unprecedented global scale, in turn placing new constraints on the D'' flow field. We test the ability of the flow model TX2008 (Simmons et al., 2009) to fit our observations. This is achieved by modelling the development of a lattice preferred orientation texture of a ppv layer subject to this flow field using a visco-plastic self consistent theory (Walker et al., 2011). Due to uncertainty in the slip system of ppv three candidate glide planes are trialled: (100)/{110}, (010), and (001). The seismic anisotropy of these models is

Supporting ITM Missions by Observing System Simulation Experiments: Initial Design, Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Yudin, V. A.; England, S.; Matsuo, T.; Wang, H.; Immel, T. J.; Eastes, R.; Akmaev, R. A.; Goncharenko, L. P.; Fuller-Rowell, T. J.; Liu, H.; Solomon, S. C.; Wu, Q.

2014-12-01

We review and discuss the capability of novel configurations of global community (WACCM-X and TIME-GCM) and planned-operational (WAM) models to support current and forthcoming space-borne missions to monitor the dynamics and composition of the Ionosphere-Thermosphere-Mesosphere (ITM) system. In the specified meteorology model configuration of WACCM-X, the lower atmosphere is constrained by operational analyses and/or short-term forecasts provided by the Goddard Earth Observing System (GEOS-5) of GMAO/NASA/GSFC. With the terrestrial weather of GEOS-5 and updated model physics, WACCM-X simulations are capable to reproduce the observed signatures of the perturbed wave dynamics and ion-neutral coupling during recent (2006-2013) stratospheric warming events, short-term, annual and year-to-year variability of prevailing flows, planetary waves, tides, and composition. With assimilation of the NWP data in the troposphere and stratosphere the planned-operational configuration of WAM can also recreate the observed features of the ITM day-to-day variability. These "terrestrial-weather" driven whole atmosphere simulations, with day-to-day variable solar and geomagnetic inputs, can provide specification of the background state (first guess) and errors for the inverse algorithms of forthcoming NASA ITM missions, such as ICON and GOLD. With two different viewing geometries (sun-synchronous, for ICON and geostationary for GOLD) these missions promise to perform complimentary global observations of temperature, winds and constituents to constrain the first-principle space weather forecast models. The paper will discuss initial designs of Observing System Simulation Experiments (OSSE) in the coupled simulations of TIME-GCM/WACCM-X/GEOS5 and WAM/GIP. As recognized, OSSE represent an excellent learning tool for designing and evaluating observing capabilities of novel sensors. The choice of assimilation schemes, forecast and observational errors will be discussed along with challenges

Evaluating Transient Global and Regional Model Simulations: Bridging the Model/Observations Information Gap

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Karl, T. R.; Easterling, D. R.; Buja, L.; Stouffer, R.; Alpert, J.

2001-05-01

A major transition in our ability to evaluate transient Global Climate Model (GCM) simulations is occurring. Real-time and retrospective numerical weather prediction analysis, model runs, climate simulations and assessments are proliferating from a handful of national centers to dozens of groups across the world. It is clear that it is no longer sufficient for any one national center to develop its data services alone. The comparison of transient GCM results with the observational climate record is difficult for several reasons. One limitation is that the global distributions of a number of basic climate quantities, such as precipitation, are not well known. Similarly, observational limitations exist with model re-analysis data. Both the NCEP/NCAR, and the ECMWF, re-analysis eliminate the problems of changing analysis systems but observational data also contain time-dependant biases. These changes in input data are blended with the natural variability making estimates of true variability uncertain. The need for data homogeneity is critical to study questions related to the ability to evaluate simulation of past climate. One approach to correct for time-dependant biases and data sparse regions is the development and use of high quality 'reference' data sets. The primary U.S. National responsibility for the archive and service of weather and climate data rests with the National Climatic Data Center (NCDC). However, as supercomputers increase the temporal and spatial resolution of both Numerical Weather Prediction (NWP) and GCM models, the volume and varied formats of data presented for archive at NCDC, using current communications technologies and data management techniques is limiting the scientific access of these data. To address this ever expanding need for climate and NWP information, NCDC along with the National Center's for Environmental Prediction (NCEP) have initiated the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is a

The RITMARE Ocean Observing System for the Italian Seas

NASA Astrophysics Data System (ADS)

Crise, A.

2016-02-01

Among its objectives, the Italian RITMARE Flagship Programme has the aim to produce a prototype of the RITMARE Ocean observing system explicitelly designed to provide a powerful infrastructure to the Italian marine science community, to help implement national and Europen environmental regulations and to contribute to the future European Ocean Observing System. The projects takes advantage of the existing platforms (fixed-point moorings, HF and X-band radars, gliders, satellite products), that constitute the basic components of the system. The structure of the RITMARE Ocean observing system is composed by a permanent component (mooring network, satellite images, HF radars) and relocatable component (gliders, drifters, relocatable infrastructures). The increasing number of available relocatable/expandable platforms allow a much larger flexibility in term of allocation of observations but requires an sampling strategy the can be modified according the scientific and socio-economic priorities. As an example, RITMARE focus is set on an experiment on the South Adriatic Pit convective area and its dynamic interactions with the adjacent Bari Canyon cascading site. (Central Mediterranean Sea). Additional effort is paid to support innovation for sensors (e.g. ship-borne LIDAR, stereo-optic directional wave detection, X-band radar innovative products), operational employment of gliders (e.g. Wave Glider) and new class of operational models. The integration can be obtained at different level: the is expected to be achieved at ICT level by defining standard interfaces (NedCDF, SOS) and catalogs in order to facilitate the discovery, viewing and downloading services of data and products. The implementation of a distributed platform-oriented RT repositories adopt a number of THREDDS web servers that act as endpoints for the RITMARE portal. The final aim is to decouple the platforms from the observations, moving from a set of observation to a suite of Essential Ocean Variables by

Observing System Simulation Experiments

NASA Technical Reports Server (NTRS)

Prive, Nikki

2015-01-01

This presentation gives an overview of Observing System Simulation Experiments (OSSEs). The components of an OSSE are described, along with discussion of the process for validating, calibrating, and performing experiments. a.

Semantic Data Integration and Ontology Use within the Global Earth Observation System of Systems (GEOSS) Global Water Cycle Data Integration System

NASA Astrophysics Data System (ADS)

Pozzi, W.; Fekete, B.; Piasecki, M.; McGuinness, D.; Fox, P.; Lawford, R.; Vorosmarty, C.; Houser, P.; Imam, B.

2008-12-01

The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so

Using Deep Learning for Targeted Data Selection, Improving Satellite Observation Utilization for Model Initialization

NASA Astrophysics Data System (ADS)

Lee, Y. J.; Bonfanti, C. E.; Trailovic, L.; Etherton, B.; Govett, M.; Stewart, J.

2017-12-01

At present, a fraction of all satellite observations are ultimately used for model assimilation. The satellite data assimilation process is computationally expensive and data are often reduced in resolution to allow timely incorporation into the forecast. This problem is only exacerbated by the recent launch of Geostationary Operational Environmental Satellite (GOES)-16 satellite and future satellites providing several order of magnitude increase in data volume. At the NOAA Earth System Research Laboratory (ESRL) we are researching the use of machine learning the improve the initial selection of satellite data to be used in the model assimilation process. In particular, we are investigating the use of deep learning. Deep learning is being applied to many image processing and computer vision problems with great success. Through our research, we are using convolutional neural network to find and mark regions of interest (ROI) to lead to intelligent extraction of observations from satellite observation systems. These targeted observations will be used to improve the quality of data selected for model assimilation and ultimately improve the impact of satellite data on weather forecasts. Our preliminary efforts to identify the ROI's are focused in two areas: applying and comparing state-of-art convolutional neural network models using the analysis data from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) weather model, and using these results as a starting point to optimize convolution neural network model for pattern recognition on the higher resolution water vapor data from GOES-WEST and other satellite. This presentation will provide an introduction to our convolutional neural network model to identify and process these ROI's, along with the challenges of data preparation, training the model, and parameter optimization.

ANALYSIS AND MODELING OF TWO FLARE LOOPS OBSERVED BY AIA AND EIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Y.; Ding, M. D.; Qiu, J.

2012-10-10

We analyze and model an M1.0 flare observed by SDO/AIA and Hinode/EIS to investigate how flare loops are heated and evolve subsequently. The flare is composed of two distinctive loop systems observed in extreme ultraviolet (EUV) images. The UV 1600 A emission at the feet of these loops exhibits a rapid rise, followed by enhanced emission in different EUV channels observed by the Atmospheric Imaging Assembly (AIA) and the EUV Imaging Spectrometer (EIS). Such behavior is indicative of impulsive energy deposit and the subsequent response in overlying coronal loops that evolve through different temperatures. Using the method we recently developed,more » we infer empirical heating functions from the rapid rise of the UV light curves for the two loop systems, respectively, treating them as two big loops with cross-sectional area of 5'' by 5'', and compute the plasma evolution in the loops using the EBTEL model. We compute the synthetic EUV light curves, which, with the limitation of the model, reasonably agree with observed light curves obtained in multiple AIA channels and EIS lines: they show the same evolution trend and their magnitudes are comparable by within a factor of two. Furthermore, we also compare the computed mean enthalpy flow velocity with the Doppler shift measurements by EIS during the decay phase of the two loops. Our results suggest that the two different loops with different heating functions as inferred from their footpoint UV emission, combined with their different lengths as measured from imaging observations, give rise to different coronal plasma evolution patterns captured both in the model and in observations.« less

Tropical convection regimes in climate models: evaluation with satellite observations

NASA Astrophysics Data System (ADS)

Steiner, Andrea K.; Lackner, Bettina C.; Ringer, Mark A.

2018-04-01

High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS) radio occultation (RO), which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

Solar System Observations with JWST

NASA Technical Reports Server (NTRS)

Norwood, James; Hammel, Heidi; Milam, Stefanie; Stansberry, John; Lunine, Jonathan; Chanover, Nancy; Hines, Dean; Sonneborn, George; Tiscareno, Matthew; Brown, Michael;

IEOOS: the Spanish Institute of Oceanography Observing System

NASA Astrophysics Data System (ADS)

Tel, Elena; Balbin, Rosa; Cabanas, Jose-Manuel; Garcia, Maria-Jesus; Garcia-Martinez, M. Carmen; Gonzalez-Pola, Cesar; Lavin, Alicia; Lopez-Jurado, Jose-Luis; Rodriguez, Carmen; Ruiz-Villarreal, Manuel; Sánchez-Leal, Ricardo F.; Vargas-Yáñez, Manuel; Vélez-Belchí, Pedro

2016-03-01

Since its foundation, 100 years ago, the Spanish Institute of Oceanography (IEO) has been observing and measuring the ocean characteristics. Here is a summary of the initiatives of the IEO in the field of the operational oceanography. Some systems like the tide gauges network has been working for more than 70 years. The standard sections began at different moments depending on the local projects, and nowadays there are more than 180 coastal stations and deep-sea ones that are systematically sampled, obtaining physical and biochemical measurements. At this moment, the Observing System includes six permanent moorings equipped with current meters, an open-sea ocean-meteorological buoy offshore Santander and a sea-surface temperature satellite image station. It also supports the Spanish contribution to the Argo international programme with 47 deployed profilers, and continuous monitoring thermosalinometers, meteorological stations and vessel-mounted acoustic Doppler current profilers on the research vessel fleet. The system is completed with the contribution to the Northwest Iberian peninsula and Gibraltar observatories, and the development of regional prediction models. All these systematic measurements allow the IEO to give responses to ocean research activities, official agencies requirements and industrial and main society demands such as navigation, resource management, risks management, recreation, as well as for management development pollution-related economic activities or marine ecosystems. All these networks are linked to international initiatives, framed largely in supranational programmes of Earth observation sponsored by the United Nations or the European Union. The synchronic observation system permits a spatio-temporal description of some events, such as new deep water formation in the Mediterranean Sea and the injection of heat to intermediate waters in the Bay of Biscay after some colder northern storms in winter 2005.

Seeing the Wood for the Trees: Applying the dual-memory system model to investigate expert teachers' observational skills in natural ecological learning environments

NASA Astrophysics Data System (ADS)

Stolpe, Karin; Björklund, Lars

2012-01-01

This study aims to investigate two expert ecology teachers' ability to attend to essential details in a complex environment during a field excursion, as well as how they teach this ability to their students. In applying a cognitive dual-memory system model for learning, we also suggest a rationale for their behaviour. The model implies two separate memory systems: the implicit, non-conscious, non-declarative system and the explicit, conscious, declarative system. This model provided the starting point for the research design. However, it was revised from the empirical findings supported by new theoretical insights. The teachers were video and audio recorded during their excursion and interviewed in a stimulated recall setting afterwards. The data were qualitatively analysed using the dual-memory system model. The results show that the teachers used holistic pattern recognition in their own identification of natural objects. However, teachers' main strategy to teach this ability is to give the students explicit rules or specific characteristics. According to the dual-memory system model the holistic pattern recognition is processed in the implicit memory system as a non-conscious match with earlier experienced situations. We suggest that this implicit pattern matching serves as an explanation for teachers' ecological and teaching observational skills. Another function of the implicit memory system is its ability to control automatic behaviour and non-conscious decision-making. The teachers offer the students firsthand sensory experiences which provide a prerequisite for the formation of implicit memories that provides a foundation for expertise.

Drought, Fire and Insects in Western US Forests: Observations to Improve Regional Land System Modeling

NASA Astrophysics Data System (ADS)

Law, B. E.; Yang, Z.; Berner, L. T.; Hicke, J. A.; Buotte, P.; Hudiburg, T. W.

2015-12-01

Drought, fire and insects are major disturbances in the western US, and conditions are expected to get warmer and drier in the future. We combine multi-scale observations and modeling with CLM4.5 to examine the effects of these disturbances on forests in the western US. We modified the Community Land Model, CLM4.5, to improve simulated drought-related mortality in forests, and prediction of insect outbreaks under future climate conditions. We examined differences in plant traits that represent species variation in sensitivity to drought, and redefined plant groupings in PFTs. Plant traits, including sapwood area: leaf area ratio and stemwood density were strongly correlated with water availability during the ecohydrologic year. Our database of co-located observations of traits for 30 tree species was used to produce parameterization of the model by species groupings according to similar traits. Burn area predicted by the new fire model in CLM4.5 compares well with recent years of GFED data, but has a positive bias compared with Landsat-based MTBS. Biomass mortality over recent decades increased, and was captured well by the model in general, but missed mortality trends of some species. Comparisons with AmeriFlux data showed that the model with dynamic tree mortality only (no species trait improvements) overestimated GPP in dry years compared with flux data at semi-arid sites, and underestimated GPP at more mesic sites that experience dry summers. Simulations with both dynamic tree mortality and species trait parameters improved estimates of GPP by 17-22%; differences between predicted and observed NEE were larger. Future projections show higher productivity from increased atmospheric CO2 and warming that somewhat offsets drought and fire effects over the next few decades. Challenges include representation of hydraulic failure in models, and availability of species trait and carbon/water process data in disturbance- and drought-impacted regions.

POD experiments using real and simulated time-sharing observations for GEO satellites in C-band transfer ranging system

NASA Astrophysics Data System (ADS)

Fen, Cao; XuHai, Yang; ZhiGang, Li; ChuGang, Feng

2016-08-01

The normal consecutive observing model in Chinese Area Positioning System (CAPS) can only supply observations of one GEO satellite in 1 day from one station. However, this can't satisfy the project need for observing many GEO satellites in 1 day. In order to obtain observations of several GEO satellites in 1 day like GPS/GLONASS/Galileo/BeiDou, the time-sharing observing model for GEO satellites in CAPS needs research. The principle of time-sharing observing model is illuminated with subsequent Precise Orbit Determination (POD) experiments using simulated time-sharing observations in 2005 and the real time-sharing observations in 2015. From time-sharing simulation experiments before 2014, the time-sharing observing 6 GEO satellites every 2 h has nearly the same orbit precision with the consecutive observing model. From POD experiments using the real time-sharing observations, POD precision for ZX12# and Yatai7# are about 3.234 m and 2.570 m, respectively, which indicates the time-sharing observing model is appropriate for CBTR system and can realize observing many GEO satellites in 1 day.

An interactive environment for the analysis of large Earth observation and model data sets

NASA Technical Reports Server (NTRS)

Bowman, Kenneth P.; Walsh, John E.; Wilhelmson, Robert B.

1993-01-01

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X DataSlice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

An interactive environment for the analysis of large Earth observation and model data sets

NASA Technical Reports Server (NTRS)

Bowman, Kenneth P.; Walsh, John E.; Wilhelmson, Robert B.

1992-01-01

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X Data Slice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

Evolution of close binary systems: Observational aspects

NASA Technical Reports Server (NTRS)

Plavec, M. J.

1981-01-01

Detached close binary systems define the main sequence band satisfactorily, but very little is known about the masses of giants and supergiants. High dispersion international ultraviolet explorer satellite observations promise an improvement, since blue companions are now frequently found to late type supergiants. Mu Sagittaril and in particular Xi Aurigae are discussed in more detail. The barium star abundance anomaly appears to be due to mass transfer in interacting systems. The symbiotic stars are another type of binary systems containing late type giants; several possible models for the hotter star and for the type of interaction are discussed. The W Serpentis stars appear to be Algols in the rapid phase of mass transfer, but a possible link relating them to the symbiotics is also indicated. Evidence of hot circumstellar plasmas has now been found in several ordinary Algols; there may exist a smooth transition between very quiescent Algols and the W Serpentis stars. Beta Lyrae is discussed in the light of new spectrophotometric results.

Experiments with data assimilation in comprehensive air quality models: Impacts on model predictions and observation requirements (Invited)

NASA Astrophysics Data System (ADS)

Mathur, R.

2009-12-01

Emerging regional scale atmospheric simulation models must address the increasing complexity arising from new model applications that treat multi-pollutant interactions. Sophisticated air quality modeling systems are needed to develop effective abatement strategies that focus on simultaneously controlling multiple criteria pollutants as well as use in providing short term air quality forecasts. In recent years the applications of such models is continuously being extended to address atmospheric pollution phenomenon from local to hemispheric spatial scales over time scales ranging from episodic to annual. The need to represent interactions between physical and chemical atmospheric processes occurring at these disparate spatial and temporal scales requires the use of observation data beyond traditional in-situ networks so that the model simulations can be reasonably constrained. Preliminary applications of assimilation of remote sensing and aloft observations within a comprehensive regional scale atmospheric chemistry-transport modeling system will be presented: (1) A methodology is developed to assimilate MODIS aerosol optical depths in the model to represent the impacts long-range transport associated with the summer 2004 Alaskan fires on surface-level regional fine particulate matter (PM2.5) concentrations across the Eastern U.S. The episodic impact of this pollution transport event on PM2.5 concentrations over the eastern U.S. during mid-July 2004, is quantified through the complementary use of the model with remotely-sensed, aloft, and surface measurements; (2) Simple nudging experiments with limited aloft measurements are performed to identify uncertainties in model representations of physical processes and assess the potential use of such measurements in improving the predictive capability of atmospheric chemistry-transport models. The results from these early applications will be discussed in context of uncertainties in the model and in the remote sensing

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Local tests of gravitation with Gaia observations of Solar System Objects

NASA Astrophysics Data System (ADS)

Hees, Aurélien; Le Poncin-Lafitte, Christophe; Hestroffer, Daniel; David, Pedro

2018-04-01

In this proceeding, we show how observations of Solar System Objects with Gaia can be used to test General Relativity and to constrain modified gravitational theories. The high number of Solar System objects observed and the variety of their orbital parameters associated with the impressive astrometric accuracy will allow us to perform local tests of General Relativity. In this communication, we present a preliminary sensitivity study of the Gaia observations on dynamical parameters such as the Sun quadrupolar moment and on various extensions to general relativity such as the parametrized post-Newtonian parameters, the fifth force formalism and a violation of Lorentz symmetry parametrized by the Standard-Model extension framework. We take into account the time sequences and the geometry of the observations that are particular to Gaia for its nominal mission (5 years) and for an extended mission (10 years).

Cloud condensation nuclei in Western Colorado: Observations and model predictions

NASA Astrophysics Data System (ADS)

Ward, Daniel Stewart

Variations in the warm cloud-active portion of atmospheric aerosols, or cloud condensation nuclei (CCN), have been shown to impact cloud droplet number concentration and subsequently cloud and precipitation processes. This issue carries special significance in western Colorado where a significant portion of the region's water resources is supplied by precipitation from winter season, orographic clouds, which are particularly sensitive to variations in CCN. Temporal and spatial variations in CCN in western Colorado were investigated using a combination of observations and a new method for modeling CCN. As part of the Inhibition of Snowfall by Pollution Aerosols (ISPA-III) field campaign, total particle and CCN number concentration were measured for a 24-day period in Mesa Verde National Park, climatologically upwind of the San Juan Mountains. These data were combined with CCN observations from Storm Peak Lab (SPL) in northwestern Colorado and from the King Air platform, flying north to south along the Western Slope. Altogether, the sampled aerosols were characteristic of a rural continental environment and the cloud-active portion varied slowly in time, and little in space. Estimates of the is hygroscopicity parameter indicated consistently low aerosol hygroscopicity typical of organic aerosol species. The modeling approach included the addition of prognostic CCN to the Regional Atmospheric Modeling System (RAMS). The RAMS droplet activation scheme was altered using parcel model simulations to include variations in aerosol hygroscopicity, represented by K. Analysis of the parcel model output and a supplemental sensitivity study showed that model CCN will be sensitive to changes in aerosol hygroscopicity, but only for conditions of low supersaturation or small particle sizes. Aerosol number, size distribution median radius, and hygroscopicity (represented by the K parameter) in RAMS were constrained by nudging to forecasts of these quantities from the Weather

Understanding Transient Forcing with Plasma Instability Model, Ionospheric Propagation Model and GNSS Observations

NASA Astrophysics Data System (ADS)

Deshpande, K.; Zettergren, M. D.; Datta-Barua, S.

2017-12-01

Fluctuations in the Global Navigation Satellite Systems (GNSS) signals observed as amplitude and phase scintillations are produced by plasma density structures in the ionosphere. Phase scintillation events in particular occur due to structures at Fresnel scales, typically about 250 meters at ionospheric heights and GNSS frequency. Likely processes contributing to small-scale density structuring in auroral and polar regions include ionospheric gradient-drift instability (GDI) and Kelvin-Helmholtz instability (KHI), which result, generally, from magnetosphere-ionosphere interactions (e.g. reconnection) associated with cusp and auroral zone regions. Scintillation signals, ostensibly from either GDI or KHI, are frequently observed in the high latitude ionosphere and are potentially useful diagnostics of how energy from the transient forcing in the cusp or polar cap region cascades, via instabilities, to small scales. However, extracting quantitative details of instabilities leading to scintillation using GNSS data drastically benefits from both a model of the irregularities and a model of GNSS signal propagation through irregular media. This work uses a physics-based model of the generation of plasma density irregularities (GEMINI - Geospace Environment Model of Ion-Neutral Interactions) coupled to an ionospheric radio wave propagation model (SIGMA - Satellite-beacon Ionospheric-scintillation Global Model of the upper Atmosphere) to explore the cascade of density structures from medium to small (sub-kilometer) scales. Specifically, GEMINI-SIGMA is used to simulate expected scintillation from different instabilities during various stages of evolution to determine features of the scintillation that may be useful to studying ionospheric density structures. Furthermore we relate the instabilities producing GNSS scintillations to the transient space and time-dependent magnetospheric phenomena and further predict characteristics of scintillation in different geophysical

Sea Ice Summer Camp: Bringing Together Arctic Sea Ice Modelers and Observers

NASA Astrophysics Data System (ADS)

Perovich, D. K.; Holland, M. M.

2016-12-01

The Arctic sea ice has undergone dramatic change and numerical models project this to continue for the foreseeable future. Understanding the mechanisms behind sea ice loss and its consequences for the larger Arctic and global systems is of critical importance if we are to anticipate and plan for the future. One impediment to progress is a disconnect between the observational and modeling communities. A sea ice summer camp was held in Barrow Alaska from 26 May to 1 June 2016 to overcome this impediment and better integrate the sea ice community. The 25 participants were a mix of modelers and observers from 13 different institutions at career stages from graduate student to senior scientist. The summer camp provided an accelerated program on sea ice observations and models and also fostered future collaborative interdisciplinary activities. Each morning was spent in the classroom with a daily lecture on an aspect of modeling or remote sensing followed by practical exercises. Topics included using models to assess sensitivity, to test hypotheses and to explore sources of uncertainty in future Arctic sea ice loss. The afternoons were spent on the ice making observations. There were four observational activities; albedo observations, ice thickness measurements, ice coring and physical properties, and ice morphology surveys. The last field day consisted of a grand challenge where the group formulated a hypothesis, developed an observational and modeling strategy to test the hypothesis, and then integrated the observations and model results. The impacts of changing sea ice are being felt today in Barrow Alaska. We opened a dialog with Barrow community members to further understand these changes. This included an evening discussion with two Barrow sea ice experts and a community presentation of our work in a public lecture at the Inupiat Heritage Center.

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data: Vegetation Carbon Density in ESMs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Xia; Hoffman, Forrest M.; Iversen, Colleen M.

Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. Here we have compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root (r = 0.71) and total vegetation (r = 0.62).more » However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S–10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1–0.8). There were substantial inconsistencies between ESM-derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.« less

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data: Vegetation Carbon Density in ESMs

DOE PAGES

Song, Xia; Hoffman, Forrest M.; Iversen, Colleen M.; ...

2017-09-09

Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. Here we have compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root (r = 0.71) and total vegetation (r = 0.62).more » However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S–10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1–0.8). There were substantial inconsistencies between ESM-derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.« less

An Observing System Simulation Experiment of assimilating leaf area index and soil moisture over cropland

NASA Astrophysics Data System (ADS)

Lafont, Sebastien; Barbu, Alina; Calvet, Jean-Christophe

2013-04-01

A Land Data Assimilation System (LDAS) is an off-line data assimilation system featuring uncoupled land surface model which is driven by observation-based atmospheric forcing. In this study the experiments were conducted with a surface externalized (SURFEX) modelling platform developed at Météo-France. It encompasses the land surface model ISBA-A-gs that simulates photosynthesis and plant growth. The photosynthetic activity depends on the vegetation types. The input soil and vegetation parameters are provided by the ECOCLIMAP II global database which assigns the ecosystem classes in several plant functional types as grassland, crops, deciduous forest and coniferous forest. New versions of the model have been recently developed in order to better describe the agricultural plant functional types. We present a set of observing system simulation experiments (OSSE) which asses leaf area index (LAI) and soil moisture assimilation for improving the land surface estimates in a controlled synthetic environment. Synthetic data were assimilated into ISBA-A-gs using an Extended Kalman Filter (EKF). This allows for an understanding of model responses to an augmentation of the number of crop types and different parameters associated to this modification. In addition, the interactions between uncertainties in the model and in the observations were investigated. This study represents the first step of a process that envisages the extension of LDAS to the new versions of the ISBA-A-gs model in order to assimilate remote sensing observations.

Important observations and parameters for a salt water intrusion model

USGS Publications Warehouse

Shoemaker, W.B.

2004-01-01

Sensitivity analysis with a density-dependent ground water flow simulator can provide insight and understanding of salt water intrusion calibration problems far beyond what is possible through intuitive analysis alone. Five simple experimental simulations presented here demonstrate this point. Results show that dispersivity is a very important parameter for reproducing a steady-state distribution of hydraulic head, salinity, and flow in the transition zone between fresh water and salt water in a coastal aquifer system. When estimating dispersivity, the following conclusions can be drawn about the data types and locations considered. (1) The "toe" of the transition zone is the most effective location for hydraulic head and salinity observations. (2) Areas near the coastline where submarine ground water discharge occurs are the most effective locations for flow observations. (3) Salinity observations are more effective than hydraulic head observations. (4) The importance of flow observations aligned perpendicular to the shoreline varies dramatically depending on distance seaward from the shoreline. Extreme parameter correlation can prohibit unique estimation of permeability parameters such as hydraulic conductivity and flow parameters such as recharge in a density-dependent ground water flow model when using hydraulic head and salinity observations. Adding flow observations perpendicular to the shoreline in areas where ground water is exchanged with the ocean body can reduce the correlation, potentially resulting in unique estimates of these parameter values. Results are expected to be directly applicable to many complex situations, and have implications for model development whether or not formal optimization methods are used in model calibration.

Important observations and parameters for a salt water intrusion model.

PubMed

Shoemaker, W Barclay

2004-01-01

Sensitivity analysis with a density-dependent ground water flow simulator can provide insight and understanding of salt water intrusion calibration problems far beyond what is possible through intuitive analysis alone. Five simple experimental simulations presented here demonstrate this point. Results show that dispersivity is a very important parameter for reproducing a steady-state distribution of hydraulic head, salinity, and flow in the transition zone between fresh water and salt water in a coastal aquifer system. When estimating dispersivity, the following conclusions can be drawn about the data types and locations considered. (1) The "toe" of the transition zone is the most effective location for hydraulic head and salinity observations. (2) Areas near the coastline where submarine ground water discharge occurs are the most effective locations for flow observations. (3) Salinity observations are more effective than hydraulic head observations. (4) The importance of flow observations aligned perpendicular to the shoreline varies dramatically depending on distance seaward from the shoreline. Extreme parameter correlation can prohibit unique estimation of permeability parameters such as hydraulic conductivity and flow parameters such as recharge in a density-dependent ground water flow model when using hydraulic head and salinity observations. Adding flow observations perpendicular to the shoreline in areas where ground water is exchanged with the ocean body can reduce the correlation, potentially resulting in unique estimates of these parameter values. Results are expected to be directly applicable to many complex situations, and have implications for model development whether or not formal optimization methods are used in model calibration.

Simultaneous Observation of Hybrid States for Cyber-Physical Systems: A Case Study of Electric Vehicle Powertrain.

PubMed

Lv, Chen; Liu, Yahui; Hu, Xiaosong; Guo, Hongyan; Cao, Dongpu; Wang, Fei-Yue

2017-08-22

As a typical cyber-physical system (CPS), electrified vehicle becomes a hot research topic due to its high efficiency and low emissions. In order to develop advanced electric powertrains, accurate estimations of the unmeasurable hybrid states, including discrete backlash nonlinearity and continuous half-shaft torque, are of great importance. In this paper, a novel estimation algorithm for simultaneously identifying the backlash position and half-shaft torque of an electric powertrain is proposed using a hybrid system approach. System models, including the electric powertrain and vehicle dynamics models, are established considering the drivetrain backlash and flexibility, and also calibrated and validated using vehicle road testing data. Based on the developed system models, the powertrain behavior is represented using hybrid automata according to the piecewise affine property of the backlash dynamics. A hybrid-state observer, which is comprised of a discrete-state observer and a continuous-state observer, is designed for the simultaneous estimation of the backlash position and half-shaft torque. In order to guarantee the stability and reachability, the convergence property of the proposed observer is investigated. The proposed observer are validated under highly dynamical transitions of vehicle states. The validation results demonstrates the feasibility and effectiveness of the proposed hybrid-state observer.

Observations and Models of Highly Intermittent Phytoplankton Distributions

PubMed Central

Mandal, Sandip; Locke, Christopher; Tanaka, Mamoru; Yamazaki, Hidekatsu

2014-01-01

The measurement of phytoplankton distributions in ocean ecosystems provides the basis for elucidating the influences of physical processes on plankton dynamics. Technological advances allow for measurement of phytoplankton data to greater resolution, displaying high spatial variability. In conventional mathematical models, the mean value of the measured variable is approximated to compare with the model output, which may misinterpret the reality of planktonic ecosystems, especially at the microscale level. To consider intermittency of variables, in this work, a new modelling approach to the planktonic ecosystem is applied, called the closure approach. Using this approach for a simple nutrient-phytoplankton model, we have shown how consideration of the fluctuating parts of model variables can affect system dynamics. Also, we have found a critical value of variance of overall fluctuating terms below which the conventional non-closure model and the mean value from the closure model exhibit the same result. This analysis gives an idea about the importance of the fluctuating parts of model variables and about when to use the closure approach. Comparisons of plot of mean versus standard deviation of phytoplankton at different depths, obtained using this new approach with real observations, give this approach good conformity. PMID:24787740

Comparison of model and human observer performance in FFDM, DBT, and synthetic mammography

NASA Astrophysics Data System (ADS)

Ikejimba, Lynda; Glick, Stephen J.; Samei, Ehsan; Lo, Joseph Y.

2016-03-01

Reader studies are important in assessing breast imaging systems. The purpose of this work was to assess task-based performance of full field digital mammography (FFDM), digital breast tomosynthesis (DBT), and synthetic mammography (SM) using different phantom types, and to determine an accurate observer model for human readers. Images were acquired on a Hologic Selenia Dimensions system with a uniform and anthropomorphic phantom. A contrast detail insert of small, low-contrast disks was created using an inkjet printer with iodine-doped ink and inserted in the phantoms. The disks varied in diameter from 210 to 630 μm, and in contrast from 1.1% contrast to 2.2% in regular increments. Human and model observers performed a 4-alternative forced choice experiment. The models were a non-prewhitening matched filter with eye model (NPWE) and a channelized Hotelling observer with either Gabor channels (Gabor-CHO) or Laguerre-Gauss channels (LG-CHO). With the given phantoms, reader scores were higher in FFDM and DBT than SM. The structure in the phantom background had a bigger impact on outcome for DBT than for FFDM or SM. All three model observers showed good correlation with humans in the uniform background, with ρ between 0.89 and 0.93. However, in the structured background, only the CHOs had high correlation, with ρ=0.92 for Gabor-CHO, 0.90 for LG-CHO, and 0.77 for NPWE. Because results of any analysis can depend on the phantom structure, conclusions of modality performance may need to be taken in the context of an appropriate model observer and a realistic phantom.

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

NASA Technical Reports Server (NTRS)

Wang, James S.; Kawa, S. Randolph; Eluszkiewicz, Janusz; Collatz, G. J.; Mountain, Marikate; Henderson, John; Nehrkorn, Thomas; Aschbrenner, Ryan; Zaccheo, T. Scott

2012-01-01

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.

ODM2 (Observation Data Model): The EarthChem Use Case

NASA Astrophysics Data System (ADS)

Lehnert, Kerstin; Song, Lulin; Hsu, Leslie; Horsburgh, Jeffrey S.; Aufdenkampe, Anthony K.; Mayorga, Emilio; Tarboton, David; Zaslavsky, Ilya

2014-05-01

PetDB is an online data system that was created in the late 1990's to serve online a synthesis of published geochemical and petrological data of igneous and metamorphic rocks. PetDB has today reached a volume of 2.5 million analytical values for nearly 70,000 rock samples. PetDB's data model (Lehnert et al., G-Cubed 2000) was designed to store sample-based observational data generated by the analysis of rocks, together with a wide range of metadata documenting provenance of the samples, analytical procedures, data quality, and data source. Attempts to store additional types of geochemical data such as time-series data of seafloor hydrothermal springs and volcanic gases, depth-series data for marine sediments and soils, and mineral or mineral inclusion data revealed the limitations of the schema: the inability to properly record sample hierarchies (for example, a garnet that is included in a diamond that is included in a xenolith that is included in a kimberlite rock sample), inability to properly store time-series data, inability to accommodate classification schemes other than rock lithologies, deficiencies of identifying and documenting datasets that are not part of publications. In order to overcome these deficiencies, PetDB has been developing a new data schema using the ODM2 information model (ODM=Observation Data Model). The development of ODM2 is a collaborative project that leverages the experience of several existing information representations, including PetDB and EarthChem, and the CUAHSI HIS Observations Data Model (ODM), as well as the general specification for encoding observational data called Observations and Measurements (O&M) to develop a uniform information model that seamlessly manages spatially discrete, feature-based earth observations from environmental samples and sample fractions as well as in-situ sensors, and to test its initial implementation in a variety of user scenarios. The O&M model, adopted as an international standard by the Open

An Evolving Model for Capacity Building with Earth Observation Imagery

NASA Astrophysics Data System (ADS)

Sylak-Glassman, E. J.

2015-12-01

For the first forty years of Earth observation satellite imagery, all imagery was collected by civilian or military governmental satellites. Over this timeframe, countries without observation satellite capabilities had very limited access to Earth observation data or imagery. In response to the limited access to Earth observation systems, capacity building efforts were focused on satellite manufacturing. Wood and Weigel (2012) describe the evolution of satellite programs in developing countries with a technology ladder. A country moves up the ladder as they move from producing satellites with training services to building satellites locally. While the ladder model may be appropriate if the goal is to develop autonomous satellite manufacturing capability, in the realm of Earth observation, the goal is generally to derive societal benefit from the use of Earth observation-derived information. In this case, the model for developing Earth observation capacity is more appropriately described by a hub-and-spoke model in which the use of Earth observation imagery is the "hub," and the "spokes" describe the various paths to achieving that imagery: the building of a satellite (either independently or with assistance), the purchase of a satellite, participation in a constellation of satellites, and the use of freely available or purchased satellite imagery. We discuss the different capacity-building activities that are conducted in each of these pathways, such as the "Know-How Transfer and Training" program developed by Surrey Satellite Technology Ltd. , Earth observation imagery training courses run by SERVIR in developing countries, and the use of national or regional remote sensing centers (such as those in Morocco, Malaysia, and Kenya) to disseminate imagery and training. In addition, we explore the factors that determine through which "spoke" a country arrives at the ability to use Earth observation imagery, and discuss best practices for achieving the capability to use

SPITFIRE within the MPI Earth system model: Model development and evaluation

NASA Astrophysics Data System (ADS)

Lasslop, Gitta; Thonicke, Kirsten; Kloster, Silvia

2014-09-01

Quantification of the role of fire within the Earth system requires an adequate representation of fire as a climate-controlled process within an Earth system model. To be able to address questions on the interaction between fire and the Earth system, we implemented the mechanistic fire model SPITFIRE, in JSBACH, the land surface model of the MPI Earth system model. Here, we document the model implementation as well as model modifications. We evaluate our model results by comparing the simulation to the GFED version 3 satellite-based data set. In addition, we assess the sensitivity of the model to the meteorological forcing and to the spatial variability of a number of fire relevant model parameters. A first comparison of model results with burned area observations showed a strong correlation of the residuals with wind speed. Further analysis revealed that the response of the fire spread to wind speed was too strong for the application on global scale. Therefore, we developed an improved parametrization to account for this effect. The evaluation of the improved model shows that the model is able to capture the global gradients and the seasonality of burned area. Some areas of model-data mismatch can be explained by differences in vegetation cover compared to observations. We achieve benchmarking scores comparable to other state-of-the-art fire models. The global total burned area is sensitive to the meteorological forcing. Adjustment of parameters leads to similar model results for both forcing data sets with respect to spatial and seasonal patterns. This article was corrected on 29 SEP 2014. See the end of the full text for details.

Towards real-time assimilation of crowdsourced observations in hydrological modeling

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Norbiato, Daniele; Monego, Martina; Ferri, Michele; Solomatine, Dimitri

2016-04-01

The continued technological advances have stimulated the spread of low-cost sensors that can be used by citizens to provide crowdsourced observations (CO) of different hydrological variables. An example of such low-cost sensors is a staff gauge connected to a QR code on which people can read the water level indication and send the measurement via a mobile phone application. The goal of this study is to assess the combined effect of the assimilation of CO coming from a distributed network of low-cost sensors, and the existing streamflow observations from physical sensors, on the performance of a semi-distributed hydrological model. The methodology is applied to the Bacchiglione catchment, North East of Italy, where an early warning system is used by the Alto Adriatico Water Authority to issue forecasted water level along the river network which cross important cities such as Vicenza and Padua. In this study, forecasted precipitation values are used as input in the hydrological model to estimate the simulated streamflow hydrograph used as boundary condition for the hydraulic model. Observed precipitation values are used to generate realistic synthetic streamflow values with various characteristics of arrival frequency and accuracy, to simulate CO coming at irregular time steps. These observations are assimilated into the semi-distributed model using a Kalman filter based method. The results of this study show that CO, asynchronous in time and with variable accuracy, can still improve flood prediction when integrated in hydrological models. When both physical and low-cost sensors are located at the same places, the assimilation of CO gives the same model improvement than the assimilation of physical observations only for high number of non-intermittent sensors. However, the integration of observations from low-cost sensors and single physical sensors can improve the flood prediction even when small a number of intermittent CO are available. This study is part of the

A proposed adaptive step size perturbation and observation maximum power point tracking algorithm based on photovoltaic system modeling

NASA Astrophysics Data System (ADS)

Huang, Yu

Solar energy becomes one of the major alternative renewable energy options for its huge abundance and accessibility. Due to the intermittent nature, the high demand of Maximum Power Point Tracking (MPPT) techniques exists when a Photovoltaic (PV) system is used to extract energy from the sunlight. This thesis proposed an advanced Perturbation and Observation (P&O) algorithm aiming for relatively practical circumstances. Firstly, a practical PV system model is studied with determining the series and shunt resistances which are neglected in some research. Moreover, in this proposed algorithm, the duty ratio of a boost DC-DC converter is the object of the perturbation deploying input impedance conversion to achieve working voltage adjustment. Based on the control strategy, the adaptive duty ratio step size P&O algorithm is proposed with major modifications made for sharp insolation change as well as low insolation scenarios. Matlab/Simulink simulation for PV model, boost converter control strategy and various MPPT process is conducted step by step. The proposed adaptive P&O algorithm is validated by the simulation results and detail analysis of sharp insolation changes, low insolation condition and continuous insolation variation.

Observations and modelling of the boundary layer using remotely piloted aircraft

NASA Astrophysics Data System (ADS)

Cayez, Gregoire; Dralet, Jean-Philippe; Seity, Yann; Momboisse, Geraud; Hattenberger, Gautier; Bronz, Murat; Roberts, Greg

2014-05-01

Over the past decade, the scientific community considers the RPAS (remotely piloted aircraft system) as a tool which can help to improve their knowledge of climate and atmospheric phenomena. RPAS equipped with instruments can now conduct measurements in areas that are too hazardous or remote for a manned plane. RPAS are especially adapted system for observing the atmospheric boundary layer processes at high vertical and temporal resolution. The main objectives of VOLTIGE (Vecteur d'Observation de La Troposphère pour l'Investigation et la Gestion de l'Environnement) are to study the life cycle of fog with micro-RPAS, encourage direct participation of the students on the advancement and development of novel observing systems, and assess the feasibility of deploying RPAS in Météo-France's operational network. The instrumented RPAS flights successfully observed the evolution of small-scale meteorological events. Before the arrival of the warm pseudo-front, profiles show a temperature inversion of a hundred meters, which overlaps a cold and wet atmospheric layer. Subsequent profiles show the combination of the arrival of a marine air mass as well as the arrival of a higher level warm pseudo-front. A third case study characterizes the warm sector of the disturbance. Two distinct air masses are visible on the vertical profiles, and show a dry air above an air almost saturated and slightly colder. The temperature and the relative humidity profiles show < 1 meter vertical resolution with a difference between ascent and descent profiles within ± 0.5°C and ± 6 % RH. These results comply with the Météo-France standard limits of quality control. The RPAS profiles were compared with those of the Arome forecast model (an operational model at Météo France). The temperature and wind in the Arome model profiles generally agree with those of the RPAS (less for relative humidity profiles). The Arome model also suggests transitions between air masses occurred at a higher

PARAGON: A Systematic, Integrated Approach to Aerosol Observation and Modeling

NASA Technical Reports Server (NTRS)

Diner, David J.; Kahn, Ralph A.; Braverman, Amy J.; Davies, Roger; Martonchik, John V.; Menzies, Robert T.; Ackerman, Thomas P.; Seinfeld, John H.; Anderson, Theodore L.; Charlson, Robert J.;

Filter accuracy for the Lorenz 96 model: Fixed versus adaptive observation operators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stuart, Andrew M.; Shukla, Abhishek; Sanz-Alonso, Daniel

In the context of filtering chaotic dynamical systems it is well-known that partial observations, if sufficiently informative, can be used to control the inherent uncertainty due to chaos. The purpose of this paper is to investigate, both theoretically and numerically, conditions on the observations of chaotic systems under which they can be accurately filtered. In particular, we highlight the advantage of adaptive observation operators over fixed ones. The Lorenz ’96 model is used to exemplify our findings. Here, we consider discrete-time and continuous-time observations in our theoretical developments. We prove that, for fixed observation operator, the 3DVAR filter can recovermore » the system state within a neighbourhood determined by the size of the observational noise. It is required that a sufficiently large proportion of the state vector is observed, and an explicit form for such sufficient fixed observation operator is given. Numerical experiments, where the data is incorporated by use of the 3DVAR and extended Kalman filters, suggest that less informative fixed operators than given by our theory can still lead to accurate signal reconstruction. Adaptive observation operators are then studied numerically; we show that, for carefully chosen adaptive observation operators, the proportion of the state vector that needs to be observed is drastically smaller than with a fixed observation operator. Indeed, we show that the number of state coordinates that need to be observed may even be significantly smaller than the total number of positive Lyapunov exponents of the underlying system.« less

Filter accuracy for the Lorenz 96 model: Fixed versus adaptive observation operators

DOE PAGES

Stuart, Andrew M.; Shukla, Abhishek; Sanz-Alonso, Daniel; ...

2016-02-23

In the context of filtering chaotic dynamical systems it is well-known that partial observations, if sufficiently informative, can be used to control the inherent uncertainty due to chaos. The purpose of this paper is to investigate, both theoretically and numerically, conditions on the observations of chaotic systems under which they can be accurately filtered. In particular, we highlight the advantage of adaptive observation operators over fixed ones. The Lorenz ’96 model is used to exemplify our findings. Here, we consider discrete-time and continuous-time observations in our theoretical developments. We prove that, for fixed observation operator, the 3DVAR filter can recovermore » the system state within a neighbourhood determined by the size of the observational noise. It is required that a sufficiently large proportion of the state vector is observed, and an explicit form for such sufficient fixed observation operator is given. Numerical experiments, where the data is incorporated by use of the 3DVAR and extended Kalman filters, suggest that less informative fixed operators than given by our theory can still lead to accurate signal reconstruction. Adaptive observation operators are then studied numerically; we show that, for carefully chosen adaptive observation operators, the proportion of the state vector that needs to be observed is drastically smaller than with a fixed observation operator. Indeed, we show that the number of state coordinates that need to be observed may even be significantly smaller than the total number of positive Lyapunov exponents of the underlying system.« less

Economic Value of an Advanced Climate Observing System

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R.; Young, D. F.; Mlynczak, M. G.

2013-12-01

Scientific missions increasingly need to show the monetary value of knowledge advances in budget-constrained environments. For example, suppose a climate science mission promises to yield decisive information on the rate of human caused global warming within a shortened time frame. How much should society be willing to pay for this knowledge today? The US interagency memo on the social cost of carbon (SCC) creates a standard yardstick for valuing damages from carbon emissions. We illustrate how value of information (VOI) calculations can be used to monetize the relative value of different climate observations. We follow the SCC, setting uncertainty in climate sensitivity to a truncated Roe and Baker (2007) distribution, setting discount rates of 2.5%, 3% and 5%, and using one of the Integrated Assessment Models sanctioned in SCC (DICE, Nordhaus 2008). We consider three mitigation scenarios: Business as Usual (BAU), a moderate mitigation response DICE Optimal, and a strong response scenario (Stern). To illustrate results, suppose that we are on the BAU emissions scenario, and that we would switch to the Stern emissions path if we learn with 90% confidence that the decadal rate of temperature change reaches or exceeds 0.2 C/decade. Under the SCC assumptions, the year in which this happens, if it happens, depends on the uncertain climate sensitivity and on the emissions path. The year in which we become 90% certain that it happens depends, in addition, on our Earth observations, their accuracy, and their completeness. The basic concept is that more accurate observations can shorten the time for societal decisions. The economic value of the resulting averted damages depends on the discount rate, and the years in which the damages occur. A new climate observation would be economically justified if the net present value (NPV) of the difference in averted damages, relative to the existing systems, exceeds the NPV of the system costs. Our results (Cooke et al. 2013

Earth observing system: 1989 reference handbook

NASA Technical Reports Server (NTRS)

1989-01-01

NASA is studying a coordinated effort called the Mission to Planet Earth to understand global change. The goals are to understand the Earth as a system, and to determine those processes that contribute to the environmental balance, as well as those that may result in changes. The Earth Observing System (Eos) is the centerpiece of the program. Eos will create an integrated scientific observing system that will enable multidisciplinary study of the Earth including the atmosphere, oceans, land surface, polar regions, and solid Earth. Science goals, the Eos data and information system, experiments, measuring instruments, and interdisciplinary investigations are described.

An Improved Ocean Observing System for Coastal Louisiana: WAVCIS (WAVE-CURRENT-SURGE Information System )

NASA Astrophysics Data System (ADS)

Zhang, X.; Stone, G. W.; Gibson, W. J.; Braud, D.

2005-05-01

WAVCIS is a regional ocean observing and forecasting system. It was designed to measure, process, forecast, and distribute oceanographic and meteorological information. WAVCIS was developed and is maintained by the Coastal Studies Institute at Louisiana State University. The in-situ observing stations are distributed along the central Louisiana and Mississippi coast. The forecast region covers the entire Gulf of Mexico with emphasis on offshore Louisiana. By using state-of-the-art instrumentation, WAVCIS measures directional waves, currents, temperature, water level, conductivity, turbidity, salinity, dissolved oxygen, chlorophyll, Meteorological parameters include wind speed and direction, air pressure and temperature visibility and humidity. Through satellite communication links, the measured data are transmitted to the WAVCIS laboratory. After processing, they are available to the public via the internet on a near real-time basis. WAVCIS also includes a forecasting capability. Waves, tides, currents, and winds are forecast daily for up to 80 hours in advance. There are a number of numerical wave and surge models that can be used for forecasts. WAM and SWAN are used for operational purposes to forecast sea state. Tides at each station are predicted based on the harmonic constants calculated from past in-situ observations at respective sites. Interpolated winds from the ETA model are used as input forcing for waves. Both in-situ and forecast information are available online to the users through WWW. Interactive GIS web mapping is implemented on the WAVCIS webpage to visualize the model output and in-situ observational data. WAVCIS data can be queried, retrieved, downloaded, and analyzed through the web page. Near real-time numerical model skill assessment can also be performed by using the data from in-situ observing stations.

General Description of Fission Observables: GEF Model Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidt, K.-H.; Jurado, B., E-mail: jurado@cenbg.in2p3.fr; Amouroux, C.

2016-01-15

The GEF (“GEneral description of Fission observables”) model code is documented. It describes the observables for spontaneous fission, neutron-induced fission and, more generally, for fission of a compound nucleus from any other entrance channel, with given excitation energy and angular momentum. The GEF model is applicable for a wide range of isotopes from Z = 80 to Z = 112 and beyond, up to excitation energies of about 100 MeV. The results of the GEF model are compared with fission barriers, fission probabilities, fission-fragment mass- and nuclide distributions, isomeric ratios, total kinetic energies, and prompt-neutron and prompt-gamma yields and energymore » spectra from neutron-induced and spontaneous fission. Derived properties of delayed neutrons and decay heat are also considered. The GEF model is based on a general approach to nuclear fission that explains a great part of the complex appearance of fission observables on the basis of fundamental laws of physics and general properties of microscopic systems and mathematical objects. The topographic theorem is used to estimate the fission-barrier heights from theoretical macroscopic saddle-point and ground-state masses and experimental ground-state masses. Motivated by the theoretically predicted early localisation of nucleonic wave functions in a necked-in shape, the properties of the relevant fragment shells are extracted. These are used to determine the depths and the widths of the fission valleys corresponding to the different fission channels and to describe the fission-fragment distributions and deformations at scission by a statistical approach. A modified composite nuclear-level-density formula is proposed. It respects some features in the superfluid regime that are in accordance with new experimental findings and with theoretical expectations. These are a constant-temperature behaviour that is consistent with a considerably increased heat capacity and an increased pairing condensation energy

Web Services as Building Blocks for an Open Coastal Observing System

NASA Astrophysics Data System (ADS)

Breitbach, G.; Krasemann, H.

2012-04-01

In coastal observing systems it is needed to integrate different observing methods like remote sensing, in-situ measurements, and models into a synoptic view of the state of the observed region. This integration can be based solely on web services combining data and metadata. Such an approach is pursued for COSYNA (Coastal Observing System for Northern and Artic seas). Data from satellite and radar remote sensing, measurements of buoys, stations and Ferryboxes are the observation part of COSYNA. These data are assimilated into models to create pre-operational forecasts. For discovering data an OGC Web Feature Service (WFS) is used by the COSYNA data portal. This Web Feature Service knows the necessary metadata not only for finding data, but in addition the URLs of web services to view and download the data. To make the data from different resources comparable a common vocabulary is needed. For COSYNA the standard names from CF-conventions are stored within the metadata whenever possible. For the metadata an INSPIRE and ISO19115 compatible data format is used. The WFS is fed from the metadata-system using database-views. Actual data are stored in two different formats, in NetCDF-files for gridded data and in an RDBMS for time-series-like data. The web service URLs are mostly standard based the standards are mainly OGC standards. Maps were created from netcdf files with the help of the ncWMS tool whereas a self-developed java servlet is used for maps of moving measurement platforms. In this case download of data is offered via OGC SOS. For NetCDF-files OPeNDAP is used for the data download. The OGC CSW is used for accessing extended metadata. The concept of data management in COSYNA will be presented which is independent of the special services used in COSYNA. This concept is parameter and data centric and might be useful for other observing systems.

Improving the Canadian Precipitation Analysis Estimates through an Observing System Simulation Experiment

NASA Astrophysics Data System (ADS)

Abbasnezhadi, K.; Rasmussen, P. F.; Stadnyk, T.

2014-12-01

To gain a better understanding of the spatiotemporal distribution of rainfall over the Churchill River basin, this study was undertaken. The research incorporates gridded precipitation data from the Canadian Precipitation Analysis (CaPA) system. CaPA has been developed by Environment Canada and provides near real-time precipitation estimates on a 10 km by 10 km grid over North America at a temporal resolution of 6 hours. The spatial fields are generated by combining forecasts from the Global Environmental Multiscale (GEM) model with precipitation observations from the network of synoptic weather stations. CaPA's skill is highly influenced by the number of weather stations in the region of interest as well as by the quality of the observations. In an attempt to evaluate the performance of CaPA as a function of the density of the weather station network, a dual-stage design algorithm to simulate CaPA is proposed which incorporates generated weather fields. More specifically, we are adopting a controlled design algorithm which is generally known as Observing System Simulation Experiment (OSSE). The advantage of using the experiment is that one can define reference precipitation fields assumed to represent the true state of rainfall over the region of interest. In the first stage of the defined OSSE, a coupled stochastic model of precipitation and temperature gridded fields is calibrated and validated. The performance of the generator is then validated by comparing model statistics with observed statistics and by using the generated samples as input to the WATFLOOD™ hydrologic model. In the second stage of the experiment, in order to account for the systematic error of station observations and GEM fields, representative errors are to be added to the reference field using by-products of CaPA's variographic analysis. These by-products explain the variance of station observations and background errors.

The Planetary Data System Information Model for Geometry Metadata

NASA Astrophysics Data System (ADS)

Guinness, E. A.; Gordon, M. K.

2014-12-01

The NASA Planetary Data System (PDS) has recently developed a new set of archiving standards based on a rigorously defined information model. An important part of the new PDS information model is the model for geometry metadata, which includes, for example, attributes of the lighting and viewing angles of observations, position and velocity vectors of a spacecraft relative to Sun and observing body at the time of observation and the location and orientation of an observation on the target. The PDS geometry model is based on requirements gathered from the planetary research community, data producers, and software engineers who build search tools. A key requirement for the model is that it fully supports the breadth of PDS archives that include a wide range of data types from missions and instruments observing many types of solar system bodies such as planets, ring systems, and smaller bodies (moons, comets, and asteroids). Thus, important design aspects of the geometry model are that it standardizes the definition of the geometry attributes and provides consistency of geometry metadata across planetary science disciplines. The model specification also includes parameters so that the context of values can be unambiguously interpreted. For example, the reference frame used for specifying geographic locations on a planetary body is explicitly included with the other geometry metadata parameters. The structure and content of the new PDS geometry model is designed to enable both science analysis and efficient development of search tools. The geometry model is implemented in XML, as is the main PDS information model, and uses XML schema for validation. The initial version of the geometry model is focused on geometry for remote sensing observations conducted by flyby and orbiting spacecraft. Future releases of the PDS geometry model will be expanded to include metadata for landed and rover spacecraft.

Modeling of coronal mass ejections with the STEREO heliospheric imagers verified with in situ observations by the Heliophysics System Observatory

NASA Astrophysics Data System (ADS)

Möstl, Christian; Isavnin, Alexey; Kilpua, Emilia; Bothmer, Volker; Mrotzek, Nicolas; Boakes, Peter; Rodriguez, Luciano; Krupar, Vratislav; Eastwood, Jonathan; Davies, Jackie; Harrison, Richard; Barnes, David; Winslow, Reka; Helcats Team

2017-04-01

We present the first study to verify modeling of CMEs as observed by the heliospheric imagers on the two STEREO spacecraft with a large scale dataset of in situ plasma and magnetic field observations from the Heliophysics System Observatory, including MESSENGER, VEX, Wind, and the in situ measurements on the two STEREO spacecraft. To this end, we have established a new interplanetary CME catalog (ICMECAT) for these spacecraft by gathering and updating individual ICME lists. In addition, we have re-calculated the in situ parameters in a consistent way, resulting in 668 events observed between 2007-2015. We then calculated the efficacy of the STEREO/HI instruments for predicting (in hindsight) with the SSEF30 model the arrival time and speed of CMEs as well as hit/miss ratios. We also show how ICMECAT gives decent statistics concerning CME impacts on all of the terrestrial planets, including Mars. The results show some major implications for future heliospheric imagers which may be used for space weather forecasting. Our effort should also serve as a baseline for the upcoming new era in heliospheric science with Solar Orbiter, Solar Probe Plus, BepiColombo returning partly comparable observations in the next decade. The presented work has received funding from the European Union Seventh Framework Programme (FP7/ 2007-2013) under grant agreement No. 606692 [HELCATS].

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the

Learning of spatial relationships between observed and imitated actions allows invariant inverse computation in the frontal mirror neuron system.

PubMed

Oh, Hyuk; Gentili, Rodolphe J; Reggia, James A; Contreras-Vidal, José L

2011-01-01

It has been suggested that the human mirror neuron system can facilitate learning by imitation through coupling of observation and action execution. During imitation of observed actions, the functional relationship between and within the inferior frontal cortex, the posterior parietal cortex, and the superior temporal sulcus can be modeled within the internal model framework. The proposed biologically plausible mirror neuron system model extends currently available models by explicitly modeling the intraparietal sulcus and the superior parietal lobule in implementing the function of a frame of reference transformation during imitation. Moreover, the model posits the ventral premotor cortex as performing an inverse computation. The simulations reveal that: i) the transformation system can learn and represent the changes in extrinsic to intrinsic coordinates when an imitator observes a demonstrator; ii) the inverse model of the imitator's frontal mirror neuron system can be trained to provide the motor plans for the imitated actions.

Observing System Simulation Experiments: An Overview

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2016-01-01

An overview of Observing System Simulation Experiments (OSSEs) will be given, with focus on calibration and validation of OSSE frameworks. Pitfalls and practice will be discussed, including observation error characteristics, incestuousness, and experimental design. The potential use of OSSEs for investigation of the behaviour of data assimilation systems will be explored, including some results from experiments using the NASAGMAO OSSE.

Optimal design of a lagrangian observing system for hydrodynamic surveys in coastal areas

NASA Astrophysics Data System (ADS)

Cucco, Andrea; Quattrocchi, Giovanni; Antognarelli, Fabio; Satta, Andrea; Maicu, Francesco; Ferrarin, Christian; Umgiesser, Georg

2014-05-01

The optimization of ocean observing systems is a pressing need for scientific research. In particular, the improvement of ocean short-term observing networks is achievable by reducing the cost-benefit ratio of the field campaigns and by increasing the quality of measurements. Numerical modeling is a powerful tool for determining the appropriateness of a specific observing system and for optimizing the sampling design. This is particularly true when observations are carried out in coastal areas and lagoons where, the use satellites is prohibitive due to the water shallowness. For such areas, numerical models are the most efficient tool both to provide a preliminary assess of the local physical environment and to make short -term predictions above its change. In this context, a test case experiment was carried out within an enclosed shallow water areas, the Cabras Lagoon (Sardinia, Italy). The aim of the experiment was to explore the optimal design for a field survey based on the use of coastal lagrangian buoys. A three-dimensional hydrodynamic model based on the finite element method (SHYFEM3D, Umgiesser et al., 2004) was implemented to simulate the lagoon water circulation. The model domain extent to the whole Cabras lagoon and to the whole Oristano Gulf, including the surrounding coastal area. Lateral open boundary conditions were provided by the operational ocean model system WMED and only wind forcing, provided by SKIRON atmospheric model (Kallos et al., 1997), was considered as surface boundary conditions. The model was applied to provide a number of ad hoc scenarios and to explore the efficiency of the short-term hydrodynamic survey. A first field campaign was carried out to investigate the lagrangian circulation inside the lagoon under the main wind forcing condition (Mistral wind from North-West). The trajectories followed by the lagrangian buoys and the estimated lagrangian velocities were used to calibrate the model parameters and to validate the

Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were appliedmore » to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.« less

OSCAR/Surface: Metadata for the WMO Integrated Observing System WIGOS

NASA Astrophysics Data System (ADS)

Klausen, Jörg; Pröscholdt, Timo; Mannes, Jürg; Cappelletti, Lucia; Grüter, Estelle; Calpini, Bertrand; Zhang, Wenjian

2016-04-01

The World Meteorological Organization (WMO) Integrated Global Observing System (WIGOS) is a key WMO priority underpinning all WMO Programs and new initiatives such as the Global Framework for Climate Services (GFCS). It does this by better integrating WMO and co-sponsored observing systems, as well as partner networks. For this, an important aspect is the description of the observational capabilities by way of structured metadata. The 17th Congress of the Word Meteorological Organization (Cg-17) has endorsed the semantic WIGOS metadata standard (WMDS) developed by the Task Team on WIGOS Metadata (TT-WMD). The standard comprises of a set of metadata classes that are considered to be of critical importance for the interpretation of observations and the evolution of observing systems relevant to WIGOS. The WMDS serves all recognized WMO Application Areas, and its use for all internationally exchanged observational data generated by WMO Members is mandatory. The standard will be introduced in three phases between 2016 and 2020. The Observing Systems Capability Analysis and Review (OSCAR) platform operated by MeteoSwiss on behalf of WMO is the official repository of WIGOS metadata and an implementation of the WMDS. OSCAR/Surface deals with all surface-based observations from land, air and oceans, combining metadata managed by a number of complementary, more domain-specific systems (e.g., GAWSIS for the Global Atmosphere Watch, JCOMMOPS for the marine domain, the WMO Radar database). It is a modern, web-based client-server application with extended information search, filtering and mapping capabilities including a fully developed management console to add and edit observational metadata. In addition, a powerful application programming interface (API) is being developed to allow machine-to-machine metadata exchange. The API is based on an ISO/OGC-compliant XML schema for the WMDS using the Observations and Measurements (ISO19156) conceptual model. The purpose of the

High pressure common rail injection system modeling and control.

PubMed

Wang, H P; Zheng, D; Tian, Y

2016-07-01

In this paper modeling and common-rail pressure control of high pressure common rail injection system (HPCRIS) is presented. The proposed mathematical model of high pressure common rail injection system which contains three sub-systems: high pressure pump sub-model, common rail sub-model and injector sub-model is a relative complicated nonlinear system. The mathematical model is validated by the software Matlab and a virtual detailed simulation environment. For the considered HPCRIS, an effective model free controller which is called Extended State Observer - based intelligent Proportional Integral (ESO-based iPI) controller is designed. And this proposed method is composed mainly of the referred ESO observer, and a time delay estimation based iPI controller. Finally, to demonstrate the performances of the proposed controller, the proposed ESO-based iPI controller is compared with a conventional PID controller and ADRC. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Regional patterns of future runoff changes from Earth system models constrained by observation

NASA Astrophysics Data System (ADS)

Yang, Hui; Zhou, Feng; Piao, Shilong; Huang, Mengtian; Chen, Anping; Ciais, Philippe; Li, Yue; Lian, Xu; Peng, Shushi; Zeng, Zhenzhong

2017-06-01

In the recent Intergovernmental Panel on Climate Change assessment, multimodel ensembles (arithmetic model averaging, AMA) were constructed with equal weights given to Earth system models, without considering the performance of each model at reproducing current conditions. Here we use Bayesian model averaging (BMA) to construct a weighted model ensemble for runoff projections. Higher weights are given to models with better performance in estimating historical decadal mean runoff. Using the BMA method, we find that by the end of this century, the increase of global runoff (9.8 ± 1.5%) under Representative Concentration Pathway 8.5 is significantly lower than estimated from AMA (12.2 ± 1.3%). BMA presents a less severe runoff increase than AMA at northern high latitudes and a more severe decrease in Amazonia. Runoff decrease in Amazonia is stronger than the intermodel difference. The intermodel difference in runoff changes is mainly caused not only by precipitation differences among models, but also by evapotranspiration differences at the high northern latitudes.

Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Tselioudis, G.; Bauer, M.; Rossow, W.

2009-04-01

Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

Big Data challenges and solutions in building the Global Earth Observation System of Systems (GEOSS)

NASA Astrophysics Data System (ADS)

Mazzetti, Paolo; Nativi, Stefano; Santoro, Mattia; Boldrini, Enrico

2014-05-01

The Group on Earth Observation (GEO) is a voluntary partnership of governments and international organizations launched in response to calls for action by the 2002 World Summit on Sustainable Development and by the G8 (Group of Eight) leading industrialized countries. These high-level meetings recognized that international collaboration is essential for exploiting the growing potential of Earth observations to support decision making in an increasingly complex and environmentally stressed world. To this aim is constructing the Global Earth Observation System of Systems (GEOSS) on the basis of a 10-Year Implementation Plan for the period 2005 to 2015 when it will become operational. As a large-scale integrated system handling large datasets as those provided by Earth Observation, GEOSS needs to face several challenges related to big data handling and big data infrastructures management. Referring to the traditional multiple Vs characteristics of Big Data (volume, variety, velocity, veracity and visualization) it is evident how most of them can be found in data handled by GEOSS. In particular, concerning Volume, Earth Observation already generates a large amount of data which can be estimated in the range of Petabytes (1015 bytes), with Exabytes (1018) already targeted. Moreover, the challenge is related not only to the data size, but also to the large amount of datasets (not necessarily having a big size) that systems need to manage. Variety is the other main challenge since datasets coming from different sensors, processed for different use-cases are published with highly heterogeneous metadata and data models, through different service interfaces. Innovative multidisciplinary applications need to access and use those datasets in a harmonized way. Moreover Earth Observation data are growing in size and variety at an exceptionally fast rate and new technologies and applications, including crowdsourcing, will even increase data volume and variety in the next future

Spectral Analysis of Forecast Error Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, N. C.; Errico, Ronald M.

2015-01-01

The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems

NASA Astrophysics Data System (ADS)

Xue, Yan; Wen, Caihong; Yang, Xiaosong; Behringer, David; Kumar, Arun; Vecchi, Gabriel; Rosati, Anthony; Gudgel, Rich

2017-08-01

The TAO/TRITON array is the cornerstone of the tropical Pacific and ENSO observing system. Motivated by the recent rapid decline of the TAO/TRITON array, the potential utility of TAO/TRITON was assessed for ENSO monitoring and prediction. The analysis focused on the period when observations from Argo floats were also available. We coordinated observing system experiments (OSEs) using the global ocean data assimilation system (GODAS) from the National Centers for Environmental Prediction and the ensemble coupled data assimilation (ECDA) from the Geophysical Fluid Dynamics Laboratory for the period 2004-2011. Four OSE simulations were conducted with inclusion of different subsets of in situ profiles: all profiles (XBT, moorings, Argo), all except the moorings, all except the Argo and no profiles. For evaluation of the OSE simulations, we examined the mean bias, standard deviation difference, root-mean-square difference (RMSD) and anomaly correlation against observations and objective analyses. Without assimilation of in situ observations, both GODAS and ECDA had large mean biases and RMSD in all variables. Assimilation of all in situ data significantly reduced mean biases and RMSD in all variables except zonal current at the equator. For GODAS, the mooring data is critical in constraining temperature in the eastern and northwestern tropical Pacific, while for ECDA both the mooring and Argo data is needed in constraining temperature in the western tropical Pacific. The Argo data is critical in constraining temperature in off-equatorial regions for both GODAS and ECDA. For constraining salinity, sea surface height and surface current analysis, the influence of Argo data was more pronounced. In addition, the salinity data from the TRITON buoys played an important role in constraining salinity in the western Pacific. GODAS was more sensitive to withholding Argo data in off-equatorial regions than ECDA because it relied on local observations to correct model biases and

Observations and NLTE modeling of Ellerman bombs

NASA Astrophysics Data System (ADS)

Berlicki, A.; Heinzel, P.

2014-07-01

Context. Ellerman bombs (EBs) are short-lived, compact, and spatially well localized emission structures that are observed well in the wings of the hydrogen Hα line. EBs are also observed in the chromospheric CaII lines and in UV continua as bright points located within active regions. Hα line profiles of EBs show a deep absorption at the line center and enhanced emission in the line wings with maxima around ±1 Å from the line center. Similar shapes of the line profiles are observed for the CaII IR line at 8542 Å. In CaII H and K lines the emission peaks are much stronger, and EBs emission is also enhanced in the line center. Aims: It is generally accepted that EBs may be considered as compact microflares located in lower solar atmosphere that contribute to the heating of these low-lying regions, close to the temperature minimum of the atmosphere. However, it is still not clear where exactly the emission of EBs is formed in the solar atmosphere. High-resolution spectrophotometric observations of EBs were used for determining of their physical parameters and construction of semi-empirical models. Obtained models allow us to determine the position of EBs in the solar atmosphere, as well as the vertical structure of the activated EB atmosphere Methods: In our analysis we used observations of EBs obtained in the Hα and CaII H lines with the Dutch Open Telescope (DOT). These one-hour long simultaneous sequences obtained with high temporal and spatial resolution were used to determine the line emissions. To analyze them, we used NLTE numerical codes for the construction of grids of 243 semi-empirical models simulating EBs structures. In this way, the observed emission could be compared with the synthetic line spectra calculated for all such models. Results: For a specific model we found reasonable agreement between the observed and theoretical emission and thus we consider such model as a good approximation to EBs atmospheres. This model is characterized by an

VLBI observations of the 0957 + 561 gravitational lens system

NASA Technical Reports Server (NTRS)

Gorenstein, M. V.; Falco, E. E.; Shapiro, I. I.; Bartel, N.; Bonometti, R. J.; Cohen, N. L.; Rogers, A. E. E.; Marcaide, J. M.; Clark, T. A.

1988-01-01

A series of VLBI observations of the gravitational lens system 0957 + 561 at a wavelength of 13 cm has yielded the positions of the A and B images, the relative magnification of their largest discernible radio structures, and the time variability of their smallest discernible radio structures. These observations have also allowed upper limits to be placed on the flux density of an expected third image. The positions and relative magnification of the A and B images provide new information with which to constrain models of the lens that forms the images. The detection of variations in the flux densities of the cores of A and B suggests that observations at shorter wavelengths may reveal superluminal motion, which may in turn provide a means to measure the relative time delay.

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

PubMed

Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

2018-02-01

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Using Evidence-Centered Design to Create a Special Educator Observation System

ERIC Educational Resources Information Center

Johnson, Evelyn S.; Crawford, Angela R.; Moylan, Laura A.; Zheng, Yuzhu

2018-01-01

The Evidence-Centered Design (ECD) framework was used to create a special education teacher observation system, Recognizing Effective Special Education Teachers (RESET). Extensive reviews of research informed the domain analysis and modeling stages, and led to the conceptual framework in which effective special education teaching is…

Performance of Versions 1,2 and 3 of the Goddard Earth Observing System (GEOS) Chemistry-Climate Model (CCM)

NASA Technical Reports Server (NTRS)

Pawson, Steven; Stolarski, Richard S.; Nielsen, J. Eric; Duncan, Bryan N.

2008-01-01

Version 1 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) was used in the first CCMVa1 model evaluation and forms the basis for several studies of links between ozone and the circulation. That version of the CCM was based on the GEOS-4 GCM. Versions 2 and 3 of the GEOS CCM are based on the GEOS-5 GCM, which retains the "Lin-Rood" dynamical core but has a totally different set of physical parameterizatiOns to GEOS-4. In Version 2 of the GEOS CCM the Goddard stratospheric chemistry module is retained. Difference between Versions 1 and 2 thus reflect the physics changes of the underlying GCMs. Several comparisons between these two models are made, several of which reveal improvements in Version 2 (including a more realistic representation of the interannual variability of the Antarctic vortex). In Version 3 of the GEOS CCM, the stratospheric chemistry mechanism is replaced by the "GMI COMBO" code that includes tropospheric chemistry and different computational approaches. An advantage of this model version. is the reduction of high ozone biases that prevail at low chlorine loadings in Versions 1 and 2. This poster will compare and contrast various aspects of the three model versions that are relevant for understanding interactions between ozone and climate.

Model Improvement by Assimilating Observations of Storm-Induced Coastal Change

NASA Astrophysics Data System (ADS)

Long, J. W.; Plant, N. G.; Sopkin, K.

2010-12-01

Discrete, large scale, meteorological events such as hurricanes can cause wide-spread destruction of coastal islands, habitats, and infrastructure. The effects can vary significantly along the coast depending on the configuration of the coastline, variable dune elevations, changes in geomorphology (sandy beach vs. marshland), and alongshore variations in storm hydrodynamic forcing. There are two primary methods of determining the changing state of a coastal system. Process-based numerical models provide highly resolved (in space and time) representations of the dominant dynamics in a physical system but must employ certain parameterizations due to computational limitations. The predictive capability may also suffer from the lack of reliable initial or boundary conditions. On the other hand, observations of coastal topography before and after the storm allow the direct quantification of cumulative storm impacts. Unfortunately these measurements suffer from instrument noise and a lack of necessary temporal resolution. This research focuses on the combination of these two pieces of information to make more reliable forecasts of storm-induced coastal change. Of primary importance is the development of a data assimilation strategy that is efficient, applicable for use with highly nonlinear models, and able to quantify the remaining forecast uncertainty based on the reliability of each individual piece of information used in the assimilation process. We concentrate on an event time-scale and estimate/update unobserved model information (boundary conditions, free parameters, etc.) by assimilating direct observations of coastal change with those simulated by the model. The data assimilation can help estimate spatially varying quantities (e.g. friction coefficients) that are often modeled as homogeneous and identify processes inadequately characterized in the model.

CATOS (Computer Aided Training/Observing System): Automating animal observation and training.

PubMed

Oh, Jinook; Fitch, W Tecumseh

2017-02-01

In animal behavioral biology, an automated observing/training system may be useful for several reasons: (a) continuous observation of animals for documentation of specific, irregular events, (b) long-term intensive training of animals in preparation for behavioral experiments, (c) elimination of potential cues and biases induced by humans during training and testing. Here, we describe an open-source-based system named CATOS (Computer Aided Training/Observing System) developed for such situations. There are several notable features in this system. CATOS is flexible and low cost because it is based on free open-source software libraries, common hardware parts, and open-system electronics based on Arduino. Automated video condensation is applied, leading to significantly reduced video data storage compared to the total active hours of the system. A data-viewing utility program helps a user browse recorded data quickly and more efficiently. With these features, CATOS has the potential to be applied to many different animal species in various environments such as laboratories, zoos, or even private homes. Also, an animal's free access to the device without constraint, and a gamified learning process, enhance the animal's welfare and enriches their environment. As a proof of concept, the system was built and tested with two different species. Initially, the system was tested for approximately 10 months with a domesticated cat. The cat was successfully and fully automatically trained to discriminate three different spoken words. Then, in order to test the system's adaptability to other species and hardware components, we used it to train a laboratory rat for 3 weeks.

Multiscale modeling of multi-decadal trends in air pollutant concentrations and their radiative properties: the role of models in an integrated observing system

NASA Astrophysics Data System (ADS)

Mathur, R.; Xing, J.; Szykman, J.; Gan, C. M.; Hogrefe, C.; Pleim, J. E.

2015-12-01

Air Pollution simulation models must address the increasing complexity arising from new model applications that treat multi-pollutant interactions across varying space and time scales. Setting and attaining lower ambient air quality standards requires an improved understanding and quantification of source attribution amongst the multiple anthropogenic and natural sources, on time scales ranging from episodic to annual and spatial scales ranging from urban to continental. Changing emission patterns over the developing regions of the world are likely to exacerbate the impacts of long-range pollutant transport on background pollutant levels, which may then impact the attainment of local air quality standards. Thus, strategies for reduction of pollution levels of surface air over a region are complicated not only by the interplay of local emissions sources and several complex physical, chemical, dynamical processes in the atmosphere, but also hemispheric background levels of pollutants. Additionally, as short-lived climate forcers, aerosols and ozone exert regionally heterogeneous radiative forcing and influence regional climate trends. EPA's coupled WRF-CMAQ modeling system is applied over a domain encompassing the northern hemisphere for the period spanning 1990-2010. This period has witnessed significant reductions in anthropogenic emissions in North America and Europe as a result of implementation of control measures and dramatic increases across Asia associated with economic and population growth, resulting in contrasting trends in air pollutant distributions and transport patterns across the northern hemisphere. Model results (trends in pollutant concentrations, optical and radiative characteristics) across the northern hemisphere are analyzed in conjunction with surface, aloft and remote sensing measurements to contrast the differing trends in air pollution and aerosol-radiation interactions in these regions over the past two decades. Given the future LEO (Trop

Towards disruptions in Earth observation? New Earth Observation systems and markets evolution: Possible scenarios and impacts

NASA Astrophysics Data System (ADS)

Denis, Gil; Claverie, Alain; Pasco, Xavier; Darnis, Jean-Pierre; de Maupeou, Benoît; Lafaye, Murielle; Morel, Eric

2017-08-01

This paper reviews the trends in Earth observation (EO) and the possible impacts on markets of the new initiatives, launched either by existing providers of EO data or by new players, privately funded. After a presentation of the existing models, the paper discusses the new approaches, addressing both commercial and institutional markets. New concepts for the very high resolution markets, in Europe and in the US, are the main focus of this analysis. Two complementary perspectives are summarised: on the one hand, the type of system and its operational performance and, on the other, the related business models, concepts of operation and ownership schemes.

An ASCA observation of the Castor system

NASA Technical Reports Server (NTRS)

Gotthelf, Eric V.; Jalota, Lalit; Mukai, Koji; White, Nicholas E.

1994-01-01

We report on a day-long ASCA broadband (1-10 keV) spectro-imaging observation of the X-ray emission from the Castor multibinary system. Significant flares were detected from both the flare star system YY Gem (Castor C) and from Castor AB located 73 sec away. Using an optimal viewing geometry and image restoration techniques, we are able to spatially resolve the emission from the two X-ray components. Broadband flare activity from Castor AB is confirmed, and quiescent flux is detected. The quiescent spectrum of YY Gem is a complex blend of emission lines across the ASCA bandpass which requires multitemperature components or two-temperature variable metal-poor abundances (approximately 5-10 below solar) to obtain a satisfactory fit to both the Mewe-Kaastra and Raymond-Smith models. The flare spectrum is consistent with an increase in the emissivity of the hotter component.

Weighting climate model projections using observational constraints.

PubMed

Gillett, Nathan P

2015-11-13

Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.

Towards An Oceanographic Component Of A Global Earth Observation System Of Systems: Progress And Challenges

NASA Astrophysics Data System (ADS)

Ackleson, S. G.

2012-12-01

Ocean observatories (systems of coordinated sensors and platforms providing real-time in situ observations across multiple temporal and spatial scales) have advanced rapidly during the past several decades with the integration of novel hardware, development of advanced cyber-infrastructures and data management software, and the formation of researcher networks employing fixed, drifting, and mobile assets. These advances have provided persistent, real-time, multi-disciplinary observations representing even the most extreme environmental conditions, enabled unique and informative views of complicated ocean processes, and aided in the development of more accurate and higher fidelity ocean models. Combined with traditional ship-based and remotely sensed observations, ocean observatories have yielded new knowledge across a broad spectrum of earth-ocean scales that would likely not exist otherwise. These developments come at a critical time in human history when the demands of global population growth are creating unprecedented societal challenges associated with rapid climatic change and unsustainable consumption of key ocean resources. Successfully meeting and overcoming these challenges and avoiding the ultimate tragedy of the commons will require greater knowledge of environmental processes than currently exists, including interactions between the ocean, the overlying atmosphere, and the adjacent land and synthesizing new knowledge into effective policy and management structures. To achieve this, researchers must have free and ready access to comprehensive data streams (oceanic, atmospheric, and terrestrial), regardless of location and collection system. While the precedent for the concept of free and open access to environmental data is not new (it traces back to the International Geophysical Year, 1957), implementing procedures and standards on a global scale is proving to be difficult, both logistically and politically. Observatories have been implemented in many

Aerosol Optical Depth over Europe: Evaluation of the CALIOPE air quality modelling system with direct-sun AERONET observations

NASA Astrophysics Data System (ADS)

Basart, Sara; Pay, María. Teresa; Pérez, Carlos; Cuevas, Emilio; Jorba, Oriol; Piot, Matthias; María Baldasano, Jose

2010-05-01

In the frame of the CALIOPE project (Baldasano et al., 2008), the Barcelona Supercomputing Center (BSC-CNS) currently operates a high-resolution air quality forecasting system based on daily photochemical forecasts in Europe (12km x 12km resolution) with the WRF-ARW/HERMES/CMAQ modelling system (http://www.bsc.es/caliope) and desert dust forecasts over Southern Europe with BSC-DREAM8b (Pérez et al., 2006; http://www.bsc.es/projects/earthscience/DREAM). High resolution simulations and forecasts are possible through their implementation on MareNostrum supercomputer at BSC-CNS. As shown in previous air quality studies (e.g. Rodríguez et al., 2001; Jiménez-Guerrero et al., 2008), the contribution of desert dust on particulate matter levels in Southern Europe is remarkable due to its proximity to African desert dust sources. When considering only anthropogenic emissions (Baldasano et al., 2008) and the current knowledge about aerosol physics and chemistry, chemistry-transport model simulations underestimate the PM10 concentrations by 30-50%. As a first approach, the natural dust contribution from BSC-DREAM8b is on-line added to the anthropogenic aerosol output of CMAQ. The aim of the present work is the quantitative evaluation of the WRF-ARW/HERMES/ CMAQ/BSC-DREAM8b forecast system to simulate the Aerosol Optical Depth (AOD) over Europe. The performance of the modelled AOD has been quantitatively evaluated with discrete and categorical (skill scores) statistics by a comparison to direct-sun AERONET observations for 2004. The contribution of different types of aerosols will be analyzed by means of the O'Neill fine mode AOD products (O'Neill et al., 2001). A previous aerosol characterization of AERONET data was performed (Basart et al., 2009) in order to discriminate the different aerosol source contributions within the study region. The results indicate a remarkable improvement in the discrete and skill-scores evaluation (accuracy, critical success index and

Landfast ice thickness in the Canadian Arctic Archipelago from observations and models

NASA Astrophysics Data System (ADS)

Howell, Stephen E. L.; Laliberté, Frédéric; Kwok, Ron; Derksen, Chris; King, Joshua

2016-07-01

Observed and modelled landfast ice thickness variability and trends spanning more than 5 decades within the Canadian Arctic Archipelago (CAA) are summarized. The observed sites (Cambridge Bay, Resolute, Eureka and Alert) represent some of the Arctic's longest records of landfast ice thickness. Observed end-of-winter (maximum) trends of landfast ice thickness (1957-2014) were statistically significant at Cambridge Bay (-4.31 ± 1.4 cm decade-1), Eureka (-4.65 ± 1.7 cm decade-1) and Alert (-4.44 ± 1.6 cm -1) but not at Resolute. Over the 50+-year record, the ice thinned by ˜ 0.24-0.26 m at Cambridge Bay, Eureka and Alert with essentially negligible change at Resolute. Although statistically significant warming in spring and fall was present at all sites, only low correlations between temperature and maximum ice thickness were present; snow depth was found to be more strongly associated with the negative ice thickness trends. Comparison with multi-model simulations from Coupled Model Intercomparison project phase 5 (CMIP5), Ocean Reanalysis Intercomparison (ORA-IP) and Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) show that although a subset of current generation models have a "reasonable" climatological representation of landfast ice thickness and distribution within the CAA, trends are unrealistic and far exceed observations by up to 2 orders of magnitude. ORA-IP models were found to have positive correlations between temperature and ice thickness over the CAA, a feature that is inconsistent with both observations and coupled models from CMIP5.

Evaluating the Ocean Component of the US Navy Earth System Model

NASA Astrophysics Data System (ADS)

Zamudio, L.

2017-12-01

Ocean currents, temperature, and salinity observations are used to evaluate the ocean component of the US Navy Earth System Model. The ocean and atmosphere components of the system are an eddy-resolving (1/12.5° equatorial resolution) version of the HYbrid Coordinate Ocean Model (HYCOM), and a T359L50 version of the NAVy Global Environmental Model (NAVGEM), respectively. The system was integrated in hindcast mode and the ocean results are compared against unassimilated observations, a stand-alone version of HYCOM, and the Generalized Digital Environment Model ocean climatology. The different observation types used in the system evaluation are: drifting buoys, temperature profiles, salinity profiles, and acoustical proxies (mixed layer depth, sonic layer depth, below layer gradient, and acoustical trapping). To evaluate the system's performance in each different metric, a scorecard is used to translate the system's errors into scores, which provide an indication of the system's skill in both space and time.

An Observing System Simulation Experiment Approach to Meteorological Network Assessment

NASA Astrophysics Data System (ADS)

Abbasnezhadi, K.; Rasmussen, P. F.; Stadnyk, T.; Boluwade, A.

2016-12-01

A proper knowledge of the spatiotemporal distribution of rainfall is important in order to conduct a mindful investigation of water movement and storage throughout a catchment. Currently, the most accurate precipitation information available for the remote Boreal ecozones of northern Manitoba is coming from the Canadian Precipitation Analysis (CaPA) data assimilation system. Throughout the Churchill River Basin (CRB), CaPA still does not have the proper skill due to the limited number of weather stations. A new approach to experimental network design was investigated based on the concept of Observing System Simulation Experiment (OSSE). The OSSE-based network assessment procedure which simulates the CaPA system provides a scientific and hydrologically significant tool to assess the sensitivity of CaPA precipitation analysis to observation network density throughout the CRB. To simulate CaPA system, synthetic background and station data were simulated, respectively, by adding spatially uncorrelated and correlated Gaussian noises to an assumingly true daily weather field synthesized by a gridded precipitation generator which simulates CaPA data. Given the true reference field on one hand, and a set of pseudo-CaPA analyses associated with different network realizations on the other hand, a WATFLOOD hydrological model was employed to compare the modeled runoff. The simulations showed that as network density increases, the accuracy of CaPA precipitation products improves up to a certain limit beyond which adding more stations to the network does not result in further accuracy.

Full Two-Body Problem Mass Parameter Observability Explored Through Doubly Synchronous Systems

NASA Astrophysics Data System (ADS)

Davis, Alex Benjamin; Scheeres, Daniel

2018-04-01

The full two-body problem (F2BP) is often used to model binary asteroid systems, representing the bodies as two finite mass distributions whose dynamics are influenced by their mutual gravity potential. The emergent behavior of the F2BP is highly coupled translational and rotational mutual motion of the mass distributions. For these systems the doubly synchronous equilibrium occurs when both bodies are tidally-locked and in a circular co-orbit. Stable oscillations about this equilibrium can be shown, for the nonplanar system, to be combinations of seven fundamental frequencies of the system and the mutual orbit rate. The fundamental frequencies arise as the linear periods of center manifolds identified about the equilibrium which are heavily influenced by each body’s mass parameters. We leverage these eight dynamical constraints to investigate the observability of binary asteroid mass parameters via dynamical observations. This is accomplished by proving the nonsingularity of the relationship between the frequencies and mass parameters for doubly synchronous systems. Thus we can invert the relationship to show that given observations of the frequencies, we can solve for the mass parameters of a target system. In so doing we are able to predict the estimation covariance of the mass parameters based on observation quality and define necessary observation accuracies for desired mass parameter certainties. We apply these tools to 617 Patroclus, a doubly synchronous Trojan binary and flyby target of the LUCY mission, as well as the Pluto and Charon system in order to predict mutual behaviors of these doubly synchronous systems and to provide observational requirements for these systems’ mass parameters

Linking Geomechanical Models with Observations of Microseismicity during CCS Operations

NASA Astrophysics Data System (ADS)

Verdon, J.; Kendall, J.; White, D.

2012-12-01

planes with arbitrary orientation (the Fracture Potential). Inelastic deformation may be incorporated within the constitutive models of the mechanical model itself in the form of plastic deformation criteria. Under such a system yield, plastic deformation, and strain hardening/weakening can be incorporated explicitly into the mechanical model, where the assumption is that the onset of inelastic processes corresponds with the onset of microseismicity within a particular element. Alternatively, an elastic geomechanical model may be used, where the resulting stress states after deformation are post-processed for a microseismicity analysis. In this paper we focus on CO2 injection for CCS and Enhanced Oil Recovery in the Weyburn Field, Canada. We generate field-scale geomechanical models to simulate the response to CO2 injection. We compare observations of microseismicity to the predictions made by the models, showing how geomechanical models can improve interpretation and understanding of microseismic observations, as well as how microseismic observations can be used to ground-truth models (a model that provides predictions with observations can be deemed more reliable than one that does not). By tuning material properties within acceptable ranges, we are able to find models that match microseismic and other geophysical observations most accurately.

Assessing Preschool Children's Competitive Behaviour: An Observational System

ERIC Educational Resources Information Center

Tsiakara, Angeliki; Digelidis, Nikolaos M.

2014-01-01

The aim of this study was to develop a direct observational system in order to assess competitive behaviours in preschool children. Participants were 176 children (90 boys, 86 girls; M[subscript age]?=?5.2 years) from 10 kindergarten classes of one town of Central Greece. A new observational system (Observational System Assessing Competition in…

Preliminary Climate Uncertainty Quantification Study on Model-Observation Test Beds at Earth Systems Grid Federation Repository

NASA Astrophysics Data System (ADS)

Lin, G.; Stephan, E.; Elsethagen, T.; Meng, D.; Riihimaki, L. D.; McFarlane, S. A.

2012-12-01

Uncertainty quantification (UQ) is the science of quantitative characterization and reduction of uncertainties in applications. It determines how likely certain outcomes are if some aspects of the system are not exactly known. UQ studies such as the atmosphere datasets greatly increased in size and complexity because they now comprise of additional complex iterative steps, involve numerous simulation runs and can consist of additional analytical products such as charts, reports, and visualizations to explain levels of uncertainty. These new requirements greatly expand the need for metadata support beyond the NetCDF convention and vocabulary and as a result an additional formal data provenance ontology is required to provide a historical explanation of the origin of the dataset that include references between the explanations and components within the dataset. This work shares a climate observation data UQ science use case and illustrates how to reduce climate observation data uncertainty and use a linked science application called Provenance Environment (ProvEn) to enable and facilitate scientific teams to publish, share, link, and discover knowledge about the UQ research results. UQ results include terascale datasets that are published to an Earth Systems Grid Federation (ESGF) repository. Uncertainty exists in observation data sets, which is due to sensor data process (such as time averaging), sensor failure in extreme weather conditions, and sensor manufacture error etc. To reduce the uncertainty in the observation data sets, a method based on Principal Component Analysis (PCA) was proposed to recover the missing values in observation data. Several large principal components (PCs) of data with missing values are computed based on available values using an iterative method. The computed PCs can approximate the true PCs with high accuracy given a condition of missing values is met; the iterative method greatly improve the computational efficiency in computing PCs

Prospects for development of unified global flood observation and prediction systems (Invited)

NASA Astrophysics Data System (ADS)

Lettenmaier, D. P.

2013-12-01

Floods are among the most damaging of natural hazards, with global flood losses in 2011 alone estimated to have exceeded $100B. Historically, flood economic damages have been highest in the developed world (due in part to encroachment on historical flood plains), but loss of life, and human impacts have been greatest in the developing world. However, as the 2011 Thailand floods show, industrializing countries, many of which do not have well developed flood protection systems, are increasingly vulnerable to economic damages as they become more industrialized. At present, unified global flood observation and prediction systems are in their infancy; notwithstanding that global weather forecasting is a mature field. The summary for this session identifies two evolving capabilities that hold promise for development of more sophisticated global flood forecast systems: global hydrologic models and satellite remote sensing (primarily of precipitation, but also of flood inundation). To this I would add the increasing sophistication and accuracy of global precipitation analysis (and forecast) fields from numerical weather prediction models. In this brief overview, I will review progress in all three areas, and especially the evolution of hydrologic data assimilation which integrates modeling and data sources. I will also comment on inter-governmental and inter-agency cooperation, and related issues that have impeded progress in the development and utilization of global flood observation and prediction systems.

State and actuator fault estimation observer design integrated in a riderless bicycle stabilization system.

PubMed

Brizuela Mendoza, Jorge Aurelio; Astorga Zaragoza, Carlos Manuel; Zavala Río, Arturo; Pattalochi, Leo; Canales Abarca, Francisco

2016-03-01

This paper deals with an observer design for Linear Parameter Varying (LPV) systems with high-order time-varying parameter dependency. The proposed design, considered as the main contribution of this paper, corresponds to an observer for the estimation of the actuator fault and the system state, considering measurement noise at the system outputs. The observer gains are computed by considering the extension of linear systems theory to polynomial LPV systems, in such a way that the observer reaches the characteristics of LPV systems. As a result, the actuator fault estimation is ready to be used in a Fault Tolerant Control scheme, where the estimated state with reduced noise should be used to generate the control law. The effectiveness of the proposed methodology has been tested using a riderless bicycle model with dependency on the translational velocity v, where the control objective corresponds to the system stabilization towards the upright position despite the variation of v along the closed-loop system trajectories. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data

NASA Technical Reports Server (NTRS)

Zeng, Xiping; Tao, Wei-Kuo; Zhang, Minghua; Peters-Lidard, Christa; Lang, Stephen; Simpson, Joanne; Kumar, Sujay; Xie, Shaocheng; Eastman, Joseph L.; Shie, Chung-Lin;

Further development of the EUMETNET Composite Observing System (EUCOS)

NASA Astrophysics Data System (ADS)

Klink, S.; Dibbern, J.

2009-09-01

EUCOS, which stands for EUMETNET Composite Observing System, is a EUMETNET programme whose main objective is a central management of surface based operational observations on a European-wide scale serving the needs of regional scale NWP. EUMETNET is a consortium of currently 26 national meteorological services in Europe that provides a framework for different operational and developmental co-operative programmes between the services. The work content of the EUCOS Programme includes the management of the operational observing networks, through the E-AMDAR, E-ASAP, E-SURFMAR and E-WINPROF programmes. The coordination of NMSs owned territorial networks (e.g. radiosonde stations and synoptic stations), data quality monitoring, fault reporting and recovery, a studies programme for the evolution of the observing networks and liaison with other organisations like WMO are among the tasks of the programme. The current period of the EUCOS programme has a five year duration (2007-2011) and a two stage approach was proposed in the programme definition. During the transition phase 2007-2008 no new programmatic objectives had been set because amongst others the Space-Terrestrial (S-T) study which investigated the relative contributions of selected space based and ground based observing systems to the forecast skill of global and regional NWP models had to be finalised first. Based on the findings of this study EUCOS currently prepares a redesign of its upper-air network. The original EUCOS upper-air network design was prepared in 2000 in order to define a set of stations serving the common general NWP requirement. Additional considerations were to make it possible to supply a common set of performance standards across the territory of EUMETNET Members and to ensure that the radiosonde network interleaved with AMDAR airports. The EUCOS upper-air network now requires a redesign because of several reasons. There is a need to take into account the significant evolution of the AMDAR

Using Flux Site Observations to Calibrate Root System Architecture Stencils for Water Uptake of Plant Functional Types in Land Surface Models.

NASA Astrophysics Data System (ADS)

Bouda, M.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.

Precise orbit determination for NASA's earth observing system using GPS (Global Positioning System)

NASA Technical Reports Server (NTRS)

Williams, B. G.

1988-01-01

An application of a precision orbit determination technique for NASA's Earth Observing System (EOS) using the Global Positioning System (GPS) is described. This technique allows the geometric information from measurements of GPS carrier phase and P-code pseudo-range to be exploited while minimizing requirements for precision dynamical modeling. The method combines geometric and dynamic information to determine the spacecraft trajectory; the weight on the dynamic information is controlled by adjusting fictitious spacecraft accelerations in three dimensions which are treated as first order exponentially time correlated stochastic processes. By varying the time correlation and uncertainty of the stochastic accelerations, the technique can range from purely geometric to purely dynamic. Performance estimates for this technique as applied to the orbit geometry planned for the EOS platforms indicate that decimeter accuracies for EOS orbit position may be obtainable. The sensitivity of the predicted orbit uncertainties to model errors for station locations, nongravitational platform accelerations, and Earth gravity is also presented.

Europlanet/IDIS: Combining Diverse Planetary Observations and Models

NASA Astrophysics Data System (ADS)

Schmidt, Walter; Capria, Maria Teresa; Chanteur, Gerard

2013-04-01

Planetary research involves a diversity of research fields from astrophysics and plasma physics to atmospheric physics, climatology, spectroscopy and surface imaging. Data from all these disciplines are collected from various space-borne platforms or telescopes, supported by modelling teams and laboratory work. In order to interpret one set of data often supporting data from different disciplines and other missions are needed while the scientist does not always have the detailed expertise to access and utilize these observations. The Integrated and Distributed Information System (IDIS) [1], developed in the framework of the Europlanet-RI project, implements a Virtual Observatory approach ([2] and [3]), where different data sets, stored in archives around the world and in different formats, are accessed, re-formatted and combined to meet the user's requirements without the need of familiarizing oneself with the different technical details. While observational astrophysical data from different observatories could already earlier be accessed via Virtual Observatories, this concept is now extended to diverse planetary data and related model data sets, spectral data bases etc. A dedicated XML-based Europlanet Data Model (EPN-DM) [4] was developed based on data models from the planetary science community and the Virtual Observatory approach. A dedicated editor simplifies the registration of new resources. As the EPN-DM is a super-set of existing data models existing archives as well as new spectroscopic or chemical data bases for the interpretation of atmospheric or surface observations, or even modeling facilities at research institutes in Europe or Russia can be easily integrated and accessed via a Table Access Protocol (EPN-TAP) [5] adapted from the corresponding protocol of the International Virtual Observatory Alliance [6] (IVOA-TAP). EPN-TAP allows to search catalogues, retrieve data and make them available through standard IVOA tools if the access to the archive

Application of the Nelson model to four timelag fuel classes using Oklahoma field observations: Model evaluation and comparison with national Fire Danger Rating System algorithms

Treesearch

J. D. Carlson; Larry S. Bradshaw; Ralph M. Nelson; Randall R Bensch; Rafal Jabrzemski

2007-01-01

The application of a next-generation dead-fuel moisture model, the 'Nelson model', to four timelag fuel classes using an extensive 21-month dataset of dead-fuel moisture observations is described. Developed by Ralph Nelson in the 1990s, the Nelson model is a dead-fuel moisture model designed to take advantage of frequent automated weather observations....

Land-cover observations as part of a Global Earth Observation System of Systems (GEOSS): Progress, activities, and prospects

USGS Publications Warehouse

Herold, M.; Woodcock, C.E.; Loveland, Thomas R.; Townshend, J.; Brady, M.; Steenmans, C.; Schmullius, C. C.

2008-01-01

The international land-cover community has been working with GEO since 2005 to build the foundations for land-cover observations as an integral part of a Global Earth Observation System of Systems (GEOSS). The Group on Earth Observation (GEO) has provided the platform to elevate the societal relevance of land cover monitoring and helped to link a diverse set of global, regional, and national activities. A dedicated 2007-2009 GEO work plan task has resulted in achievements on the strategic and implementation levels. Integrated Global Observations of the Land (IGOL), the land theme of the Integrated Global Observation Strategy (IGOS), has been approved and is now in the process of transition into GEO implementation. New global land-cover maps at moderate spatial resolutions (i.e., GLOBCOVER) are being produced using guidelines and standards of the international community. The Middecadal Global Landsat Survey for 2005-2006 is extending previous 1990 and 2000 efforts for global, high-quality Landsat data. Despite this progress, essential challenges for building a sustained global land-cover-observing system remain, including: international cooperation on the continuity of global observations; ensuring consistency in land monitoring approaches; community engagement and country participation in mapping activities; commitment to ongoing quality assurance and validation; and regional networking and capacity building.

Einstein X-ray observations of QSO's with absorption-line systems

NASA Technical Reports Server (NTRS)

Junkkarinen, V. T.; Marscher, A. P.; Burbidge, E. M.

1982-01-01

The detection of X-ray emission from eight QSO's is reported, plus an upper limit to the X-ray flux from one QSO, using the Einstein X-ray Observatory (HEAO-2). Each object in the sample contains at least one absorption-line system that has been identified in its optical spectrum. The present results are combined with those of other investigators to form a sample of 44 absorption-line QSO's (with 2 sub e greater than 1.2) which have been observed in the X-ray. This sample cannot be distinguished, in terms of X-ray properties, from one which consists of QSO's in which no absorption systems have been identified. These results are consistent with extrinsic models for absorption-line clouds, as well as with current versions of intrinsic models.

Lagrangian Observations and Modeling of Marine Larvae

NASA Astrophysics Data System (ADS)

Paris, Claire B.; Irisson, Jean-Olivier

2017-04-01

Just within the past two decades, studies on the early-life history stages of marine organisms have led to new paradigms in population dynamics. Unlike passive plant seeds that are transported by the wind or by animals, marine larvae have motor and sensory capabilities. As a result, marine larvae have a tremendous capacity to actively influence their dispersal. This is continuously revealed as we develop new techniques to observe larvae in their natural environment and begin to understand their ability to detect cues throughout ontogeny, process the information, and use it to ride ocean currents and navigate their way back home, or to a place like home. We present innovative in situ and numerical modeling approaches developed to understand the underlying mechanisms of larval transport in the ocean. We describe a novel concept of a Lagrangian platform, the Drifting In Situ Chamber (DISC), designed to observe and quantify complex larval behaviors and their interactions with the pelagic environment. We give a brief history of larval ecology research with the DISC, showing that swimming is directional in most species, guided by cues as diverse as the position of the sun or the underwater soundscape, and even that (unlike humans!) larvae orient better and swim faster when moving as a group. The observed Lagrangian behavior of individual larvae are directly implemented in the Connectivity Modeling System (CMS), an open source Lagrangian tracking application. Simulations help demonstrate the impact that larval behavior has compared to passive Lagrangian trajectories. These methodologies are already the base of exciting findings and are promising tools for documenting and simulating the behavior of other small pelagic organisms, forecasting their migration in a changing ocean.

Evaluation of atmospheric dust prediction models using ground-based observations

NASA Astrophysics Data System (ADS)

Terradellas, Enric; María Baldasano, José; Cuevas, Emilio; Basart, Sara; Huneeus, Nicolás; Camino, Carlos; Dundar, Cinhan; Benincasa, Francesco

2013-04-01

An important step in numerical prediction of mineral dust is the model evaluation aimed to assess its performance to forecast the atmospheric dust content and to lead to new directions in model development and improvement. The first problem to address the evaluation is the scarcity of ground-based routine observations intended for dust monitoring. An alternative option would be the use of satellite products. They have the advantage of a large spatial coverage and a regular availability. However, they do have numerous drawbacks that make the quantitative retrievals of aerosol-related variables difficult and imprecise. This work presents the use of different ground-based observing systems for the evaluation of dust models in the Regional Center for Northern Africa, Middle East and Europe of the World Meteorological Organization (WMO) Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS). The dust optical depth at 550 nm forecast by different models is regularly compared with the AERONET measurements of Aerosol Optical Depth (AOD) for 40 selected stations. Photometric measurements are a powerful tool for remote sensing of the atmosphere allowing retrieval of aerosol properties, such as AOD. This variable integrates the contribution of different aerosol types, but may be complemented with spectral information that enables hypotheses about the nature of the particles. Comparison is restricted to cases with low Ångström exponent values in order to ensure that coarse mineral dust is the dominant aerosol type. Additionally to column dust load, it is important to evaluate dust surface concentration and dust vertical profiles. Air quality monitoring stations are the main source of data for the evaluation of surface concentration. However they are concentrated in populated and industrialized areas around the Mediterranean. In the present contribution, results of different models are compared with observations of PM10 from the Turkish air quality network for

Air Modeling - Observational Meteorological Data

EPA Pesticide Factsheets

Observed meteorological data for use in air quality modeling consist of physical parameters that are measured directly by instrumentation, and include temperature, dew point, wind direction, wind speed, cloud cover, cloud layer(s), ceiling height,

Brief History of Agricultural Systems Modeling

NASA Technical Reports Server (NTRS)

Jones, James W.; Antle, John M.; Basso, Bruno O.; Boote, Kenneth J.; Conant, Richard T.; Foster, Ian; Godfray, H. Charles J.; Herrrero, Mario; Howitt, Richard E.; Janssen, Sandor;

Brief history of agricultural systems modeling.

PubMed

Jones, James W; Antle, John M; Basso, Bruno; Boote, Kenneth J; Conant, Richard T; Foster, Ian; Godfray, H Charles J; Herrero, Mario; Howitt, Richard E; Janssen, Sander; Keating, Brian A; Munoz-Carpena, Rafael; Porter, Cheryl H; Rosenzweig, Cynthia; Wheeler, Tim R

2017-07-01

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be

1993 Earth Observing System reference handbook

NASA Technical Reports Server (NTRS)

Asrar, Ghassem (Editor); Dokken, David Jon (Editor)

1993-01-01

Mission to Planet Earth (MTPE) is a NASA-sponsored concept that uses space- and ground-based measurement systems to provide the scientific basis for understanding global change. The space-based components of MTPE will provide a constellation of satellites to monitor the Earth from space. Sustained observations will allow researchers to monitor climate variables overtime to determine trends; however, space-based monitoring alone is not sufficient. A comprehensive data and information system, a community of scientists performing research with the data acquired, and extensive ground campaigns are all important components. Brief descriptions of the various elements that comprise the overall mission are provided. The Earth Observing System (EOS) - a series of polar-orbiting and low-inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans - is the centerpiece of MTPE. The elements comprising the EOS mission are described in detail.

Western Greenland Subglacial Hydrologic Modeling and Observables: Seismicity and GPS

NASA Astrophysics Data System (ADS)

Carmichael, J. D.; Joughin, I. R.

2010-12-01

I present a hydro-mechanical model of the Western Greenland ice sheet with surface observables for two modes of meltwater input. Using input prescribed from distributed surface data, First, I bound the subglacial carrying capacity for both a distributed and localized system, in a typical summer. I provide observations of the ambient seismic response and its support for an established surface-to-bed connection. Second, I show the ice sheet response to large impulsive hydraulic inputs (lake drainage events) should produce distinct seismic observables that depend upon the localization of the drainage systems. In the former case, the signal propagates as a diffusive wave, while the channelized case, the response is localized. I provide a discussion of how these results are consistent with previous reports (Das et al, 2008, Joughin et al, 2008) of melt-induced speedup along Greenland's Western Flank. Late summer seismicity for a four-receiver array deployed near a supraglacial lake, 68 44.379N, 49 30.064W. Clusters of seismic activity are characterized by dominant shear-wave energy, consistent with basal sliding events.

Development of the AuScope Australian Earth Observing System

NASA Astrophysics Data System (ADS)

Rawling, T.

2017-12-01

Advances in monitoring technology and significant investment in new national research initiatives, will provide significant new opportunities for delivery of novel geoscience data streams from across the Australian continent over the next decade. The AuScope Australian Earth Observing System (AEOS) is linking field and laboratory infrastructure across Australia to form a national sensor array focusing on the Solid Earth. As such AuScope is working with these programs to deploy observational infrastructure, including MT, passive seismic, and GNSS networks across the entire Australian Continent. Where possible the observational grid will be co-located with strategic basement drilling in areas of shallow cover and tied with national reflection seismic and sampling transects. This integrated suite of distributed earth observation and imaging sensors will provide unprecedented imaging fidelity of our crust, across all length and time scales, to fundamental and applied researchers in the earth, environmental and geospatial sciences. The AEOS will the Earth Science community's Square Kilometer Array (SKA) - a distributed telescope that looks INTO the earth rather than away from it - a 10 million SKA. The AEOS is strongly aligned with other community strategic initiatives including the UNCOVER research program as well as other National Collaborative Research Infrastructure programs such as the Terrestrial Environmental Research Network (TERN) and the Integrated Marine Observing System (IMOS) providing an interdisciplinary collaboration platform across the earth and environmental sciences. There is also very close alignment between AuScope and similar international programs such as EPOS, the USArray and EarthCube - potential collaborative linkages we are currently in the process of pursuing more fomally. The AuScope AEOS Infrastructure System is ultimately designed to enable the progressive construction, refinement and ongoing enrichment of a live, "FAIR" four

Implementing CUAHSI and SWE observation data models in the long-term monitoring infrastructure TERENO

NASA Astrophysics Data System (ADS)

Klump, J. F.; Stender, V.; Schroeder, M.

2013-12-01

) about the data values in combination with information about the sensor systems. Also the CUAHSI model is supported by a large and active international user community. The 52° North SOS data model can be modeled as a sub-set of the CUHASI data model. In our implementation the 52° North SWE data model is implemented as database views of the CUHASI model to avoid redundant data storage. An essential aspect in TERENO Northeast is the use of standard OGS web services to facilitate data exchange and interoperability. A uniform treatment of sensor data can be realized through OGC Sensor Web Enablement (SWE) which makes a number of standards and interface definitions available: Observation & Measurement (O&M) model for the description of observations and measurements, Sensor Model Language (SensorML) for the description of sensor systems, Sensor Observation Service (SOS) for obtaining sensor observations, Sensor Planning Service (SPS) for tasking sensors, Web Notification Service (WNS) for asynchronous dialogues and Sensor Alert Service (SAS) for sending alerts.

Observing and Modeling Earth's Energy Flows

NASA Astrophysics Data System (ADS)

Stevens, Bjorn; Schwartz, Stephen E.

2012-07-01

This article reviews, from the authors' perspective, progress in observing and modeling energy flows in Earth's climate system. Emphasis is placed on the state of understanding of Earth's energy flows and their susceptibility to perturbations, with particular emphasis on the roles of clouds and aerosols. More accurate measurements of the total solar irradiance and the rate of change of ocean enthalpy help constrain individual components of the energy budget at the top of the atmosphere to within ±2 W m-2. The measurements demonstrate that Earth reflects substantially less solar radiation and emits more terrestrial radiation than was believed even a decade ago. Active remote sensing is helping to constrain the surface energy budget, but new estimates of downwelling surface irradiance that benefit from such methods are proving difficult to reconcile with existing precipitation climatologies. Overall, the energy budget at the surface is much more uncertain than at the top of the atmosphere. A decade of high-precision measurements of the energy budget at the top of the atmosphere is providing new opportunities to track Earth's energy flows on timescales ranging from days to years, and at very high spatial resolution. The measurements show that the principal limitation in the estimate of secular trends now lies in the natural variability of the Earth system itself. The forcing-feedback-response framework, which has developed to understand how changes in Earth's energy flows affect surface temperature, is reviewed in light of recent work that shows fast responses (adjustments) of the system are central to the definition of the effective forcing that results from a change in atmospheric composition. In many cases, the adjustment, rather than the characterization of the compositional perturbation (associated, for instance, with changing greenhouse gas concentrations, or aerosol burdens), limits accurate determination of the radiative forcing. Changes in clouds contribute

The H,G_1,G_2 photometric system with scarce observational data

NASA Astrophysics Data System (ADS)

Penttilä, A.; Granvik, M.; Muinonen, K.; Wilkman, O.

2014-07-01

The H,G_1,G_2 photometric system was officially adopted at the IAU General Assembly in Beijing, 2012. The system replaced the H,G system from 1985. The 'photometric system' is a parametrized model V(α; params) for the magnitude-phase relation of small Solar System bodies, and the main purpose is to predict the magnitude at backscattering, H := V(0°), i.e., the (absolute) magnitude of the object. The original H,G system was designed using the best available data in 1985, but since then new observations have been made showing certain features, especially near backscattering, to which the H,G function has troubles adjusting to. The H,G_1,G_2 system was developed especially to address these issues [1]. With a sufficient number of high-accuracy observations and with a wide phase-angle coverage, the H,G_1,G_2 system performs well. However, with scarce low-accuracy data the system has troubles producing a reliable fit, as would any other three-parameter nonlinear function. Therefore, simultaneously with the H,G_1,G_2 system, a two-parameter version of the model, the H,G_{12} system, was introduced [1]. The two-parameter version ties the parameters G_1,G_2 into a single parameter G_{12} by a linear relation, and still uses the H,G_1,G_2 system in the background. This version dramatically improves the possibility to receive a reliable phase-curve fit to scarce data. The amount of observed small bodies is increasing all the time, and so is the need to produce estimates for the absolute magnitude/diameter/albedo and other size/composition related parameters. The lack of small-phase-angle observations is especially topical for near-Earth objects (NEOs). With these, even the two- parameter version faces problems. The previous procedure with the H,G system in such circumstances has been that the G-parameter has been fixed to some constant value, thus only fitting a single-parameter function. In conclusion, there is a definitive need for a reliable procedure to produce

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations.