Assimilation of global versus local data sets into a regional model of the Gulf Stream system: 1. Data effectiveness

1995 ◽  
Vol 100 (C12) ◽  
pp. 24773 ◽  
Author(s):  
Paola Malanotte-Rizzoli ◽  
Roberta E. Young
Keyword(s):  
Gulf Stream ◽  
Regional Model ◽  
Data Sets ◽  
Local Data ◽  
Stream System ◽  
System 1

Fresh water balance of the Gulf Stream system in a regional model study

2001 ◽  
Vol 18 (1-2) ◽  
pp. 17-27 ◽  
Author(s):  
R. Gerdes ◽  
A. Biastoch ◽  
R. Redler
Keyword(s):  
Water Balance ◽  
Fresh Water ◽  
Gulf Stream ◽  
Regional Model ◽  
Model Study ◽  
Stream System

scholarly journals An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Mustafa Yuksel ◽  
Suat Gonul ◽  
Gokce Banu Laleci Erturkmen ◽  
Ali Anil Sinaci ◽  
Paolo Invernizzi ◽  
...  
Keyword(s):  
Real Life ◽  
Case Series ◽  
Background Information ◽  
Data Sets ◽  
Local Data ◽  
Lombardy Region ◽  
Common Information ◽  
Spontaneous Reports ◽  
Wide Range ◽  
Common Information Model

Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information.

scholarly journals Interactive coupling of regional atmosphere with biosphere in the new generation regional climate system model REMO-iMOVE

2014 ◽  
Vol 7 (3) ◽  
pp. 1093-1114 ◽  
Author(s):  
C. Wilhelm ◽  
D. Rechid ◽  
D. Jacob
Keyword(s):  
Land Surface ◽  
Regional Climate ◽  
Regional Model ◽  
Horizontal Resolution ◽  
Soil Conditions ◽  
Data Sets ◽  
Vegetation Phenology ◽  
Land Surface Scheme ◽  
New Model ◽  
Surface Scheme

Abstract. The main objective of this study is the coupling of the regional climate model REMO with a new land surface scheme including dynamic vegetation phenology, and the evaluation of the new model version called REMO with interactive MOsaic-based VEgetation: REMO-iMOVE. First, we focus on the documentation of the technical aspects of the new model constituents and the coupling mechanism. The representation of vegetation in iMOVE is based on plant functional types (PFTs). Their geographical distribution is prescribed to the model which can be derived from different land surface data sets. Here, the PFT distribution is derived from the GLOBCOVER 2000 data set which is available on 1 km × 1 km horizontal resolution. Plant physiological processes like photosynthesis, respiration and transpiration are incorporated into the model. The vegetation modules are fully coupled to atmosphere and soil. In this way, plant physiological activity is directly driven by atmospheric and soil conditions at the model time step (two minutes to some seconds). In turn, the vegetation processes and properties influence the exchange of substances, energy and momentum between land and atmosphere. With the new coupled regional model system, dynamic feedbacks between vegetation, soil and atmosphere are represented at regional to local scale. In the evaluation part, we compare simulation results of REMO-iMOVE and of the reference version REMO2009 to multiple observation data sets of temperature, precipitation, latent heat flux, leaf area index and net primary production, in order to investigate the sensitivity of the regional model to the new land surface scheme and to evaluate the performance of both model versions. Simulations for the regional model domain Europe on a horizontal resolution of 0.44° had been carried out for the time period 1995–2005, forced with ECMWF ERA-Interim reanalyses data as lateral boundary conditions. REMO-iMOVE is able to simulate the European climate with the same quality as the parent model REMO2009. Differences in near-surface climate parameters can be restricted to some regions and are mainly related to the new representation of vegetation phenology. The seasonal and interannual variations in growth and senescence of vegetation are captured by the model. The net primary productivity lies in the range of observed values for most European regions. This study reveals the need for implementing vertical soil water dynamics in order to differentiate the access of plants to water due to different rooting depths. This gets especially important if the model will be used in dynamic vegetation studies.

scholarly journals Modeling the Gulf Stream System: How far from reality?

1996 ◽  
Vol 23 (22) ◽  
pp. 3155-3158 ◽  
Author(s):  
Yi Chao ◽  
Avijit Gangopadhyay ◽  
Frank O. Bryan ◽  
William R. Holland
Keyword(s):  
Gulf Stream ◽  
Stream System

Local Data for Obesity Prevention: Using National Data Sets

2011 ◽  
Vol 63 (4) ◽  
pp. 550-559 ◽  
Author(s):  
Anwar T. Merchant ◽  
Patrick DeLuca ◽  
Mamdouh M. Shubair ◽  
Julie Emili ◽  
Pavlos Kanaroglou
Keyword(s):  
Obesity Prevention ◽  
Data Sets ◽  
National Data ◽  
Local Data

scholarly journals Multi-site evaluation of the JULES land surface model using global and local data

2015 ◽  
Vol 8 (2) ◽  
pp. 295-316 ◽  
Author(s):  
D. Slevin ◽  
S. F. B. Tett ◽  
M. Williams
Keyword(s):  
Land Surface ◽  
Meteorological Data ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Data Sets ◽  
Local Data ◽  
Area Index ◽  
Phenology Model ◽  
Global Data

Abstract. This study evaluates the ability of the JULES land surface model (LSM) to simulate photosynthesis using local and global data sets at 12 FLUXNET sites. Model parameters include site-specific (local) values for each flux tower site and the default parameters used in the Hadley Centre Global Environmental Model (HadGEM) climate model. Firstly, gross primary productivity (GPP) estimates from driving JULES with data derived from local site measurements were compared to observations from the FLUXNET network. When using local data, the model is biased with total annual GPP underestimated by 16% across all sites compared to observations. Secondly, GPP estimates from driving JULES with data derived from global parameter and atmospheric reanalysis (on scales of 100 km or so) were compared to FLUXNET observations. It was found that model performance decreases further, with total annual GPP underestimated by 30% across all sites compared to observations. When JULES was driven using local parameters and global meteorological data, it was shown that global data could be used in place of FLUXNET data with a 7% reduction in total annual simulated GPP. Thirdly, the global meteorological data sets, WFDEI and PRINCETON, were compared to local data to find that the WFDEI data set more closely matches the local meteorological measurements (FLUXNET). Finally, the JULES phenology model was tested by comparing results from simulations using the default phenology model to those forced with the remote sensing product MODIS leaf area index (LAI). Forcing the model with daily satellite LAI results in only small improvements in predicted GPP at a small number of sites, compared to using the default phenology model.

scholarly journals Design and Analysis of a Relational Database for Behavioral Experiments Data Processing

2018 ◽  
Vol 14 (02) ◽  
pp. 117 ◽  
Author(s):  
Radoslava Stankova Kraleva ◽  
Velin Spasov Kralev ◽  
Nina Sinyagina ◽  
Petia Koprinkova-Hristova ◽  
Nadejda Bocheva
Keyword(s):  
Data Storage ◽  
Relational Database ◽  
Database Management System ◽  
Data Sets ◽  
Behavioral Experiments ◽  
Local Data ◽  
Specific Data ◽  
Binary File ◽  
Different Types ◽  
The One

In this paper, the results of a comparative analysis between different approaches to experimental data storage and processing are presented. Several studies related to the problem and some methods for solving it have been discussed. Different types of databases, ways of using them and the areas of their application are analyzed. For the purposes of the study, a relational database for storing and analyzing a specific data from behavioral experiments was designed. The methodology and conditions for conducting the experiments are described. Three different indicators were analyzed, respectively: memory required to store the data, time to load the data from an external file into computer memory and iteration time across all records through one cycle. The obtained results show that for storing a large number of records (in the order of tens of millions of rows), either dynamic arrays (stored on external media in binary file format), or an approach based on a local or remote database management system can be used. Regarding the data loading time, the fastest approach was the one that uses dynamic arrays. It outperforms significantly the approaches based on a local or remote database. The obtained results show that the dynamic arrays and the local data sets approaches iterated much faster across all data records than the remote database approach. The paper concludes with proposal for further developments towards using of web services.

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