Ionospheric Characteristics for Archiving at the World Data Centers

1990 ◽  
Author(s):  
Robert R. Gamache ◽  
Bodo W. Reinisch
Keyword(s):  
Data Centers ◽  
World Data ◽  
The World

scholarly journals A Note On Errors and Uncertainties in NCAR Aircraft Pyrgeometer Data from MONEX

1982 ◽  
Vol 63 (12) ◽  
pp. 1387-1389 ◽  
Author(s):  
Robert G. Ellingson
Keyword(s):  
Data Centers ◽  
World Data ◽  
Downward Flux ◽  
The World ◽  
Corrected Data ◽  
Irradiance Data

An analysis of the infrared irradiance data obtained from the upward- and downward-looking pyrgeometers on the NCAR Electra indicates that there are nonsystematic errors in the Monsoon Experiment (MONEX) data archived at the World Data Centers. The errors often exceed 8% of the downward flux and may be eliminated only by reanalyzing the 1 Hz data archived at NCAR. In addition, uncertainties in the measurement of the temperatures of the pyrgeometer surfaces lead to uncertainties in the corrected data, which may be important to particular applications.

scholarly journals Automatic procedures for submitting essential climate variables (ECVs) recorded at Italian Atmospheric Observatories to WMO/GAW data centers

2018 ◽  
Author(s):  
Luca Naitza ◽  
Davide Putero ◽  
Angela Marinoni ◽  
Francescopiero Calzolari ◽  
Fabrizio Roccato ◽  
...  
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Data Dissemination ◽  
Meteorological Data ◽  
Climate Variables ◽  
Near Surface ◽  
World Data ◽  
The World ◽  
Data Production ◽  
Reactive Gases

Abstract. In the framework of the National Project of Interest Nextdata, we developed procedures for the automatic flagging and formatting of trace gas, atmospheric aerosol and meteorological data to be submitted to Global Atmosphere Watch programme by the World Meteorological Organization (WMO/GAW). In this work, we describe a first prototype of a centralized system to support Italian atmospheric observatories towards a more efficient and objective data production and subsequent submission to WMO/GAW World Data Centers (WDCs). In particular, the atmospheric variables covered by this work were focused on near-surface trace gases, aerosol properties and (ancillary) meteorological parameters which are under the umbrella of the World Data Center for Greenhouse Gases (WDCGG, see https://ds.data.jma.go.jp/gmd/wdcgg/), World Data Center for Reactive Gases and World Data Center for Aerosol (WDCRG and WDCA, see http://ebas.nilu.no). For different Essential Climate Variables (ECVs), we developed specific routines for data filtering, flagging, format harmonization and creation of data products (i.e. plot of raw and valid-corrected-averaged ECV data and internal instrument parameters) useful for detecting instrumental problems or atmospheric events. A special suite of products based on the temporal aggregation of valid ECV data (like the “calendar” or “timevariation” products) were implemented for quick data dissemination towards stakeholders or citizens Currently, the automatic processing of data is active for a subset of ECVs and 4 measurement sites in Italy. The Nextdata system does not generate “consolidated” data to be directly submitted to WDCs, but it represents a valuable tool to facilitate data providers towards a more efficient data production for those data streams. Our effort is expected to accelerate the process of data submission to GAW/WMO or to other reference data centers or repositories as well as to make the data flagging more “objective”, which means that it is based on a set of well-defined selection criteria and not strictly related to the subjective judgment of station operators. Moreover, the adoption of automatic procedures for data flagging and data correction allows to keep track of the process that led to the final validated data, and makes data evaluation and revisions more efficient.

ANALISIS DETERMINAN KUALITAS LINGKUNGAN PERIODE 1999-2013

2016 ◽  
Vol 21 (1) ◽  
pp. 9-20
Author(s):  
Ersalina Tang
Keyword(s):  
Foreign Direct Investment ◽  
Energy Consumption ◽  
Gross Domestic Product ◽  
Co2 Emissions ◽  
Direct Investment ◽  
Meat Consumption ◽  
Domestic Product ◽  
World Data ◽  
The World ◽  
The Impact

The purpose of this study is to analyze the impact of Foreign Direct Investment, Gross Domestic Product, Energy Consumption, Electric Consumption, and Meat Consumption on CO2 emissions of 41 countries in the world using panel data from 1999 to 2013. After analyzing 41 countries in the world data, furthermore 17 countries in Asia was analyzed with the same period. This study utilized quantitative approach with Ordinary Least Square (OLS) regression method. The results of 41 countries in the world data indicates that Foreign Direct Investment, Gross Domestic Product, Energy Consumption, and Meat Consumption significantlyaffect Environmental Qualities which measured by CO2 emissions. Whilst the results of 17 countries in Asia data implies that Foreign Direct Investment, Energy Consumption, and Electric Consumption significantlyaffect Environmental Qualities. However, Gross Domestic Product and Meat Consumption does not affect Environmental Qualities.

The Electronic Geophysical Year (eGY) and the World Data Center System

2008 ◽  
Vol 10 (2) ◽  
pp. 1-4
Author(s):  
D. Clark ◽  
B. Minster ◽  
E. A. Kihn
Keyword(s):  
Data Center ◽  
World Data ◽  
The World

scholarly journals The Origins and Principles of the World Data Center System

2010 ◽  
Vol 8 ◽  
pp. IGY55-IGY65 ◽  
Author(s):  
F.L. Korsmo
Keyword(s):  
Data Center ◽  
World Data ◽  
The World

World Data Centers (Oceanography) (WDC)

1981 ◽  
pp. 534-539
Author(s):  
Kamil A. Bekiashev ◽  
Vitali V. Serebriakov
Keyword(s):  
Data Centers ◽  
World Data

Energy and SLA Efficient Virtual Machine Placement in Cloud Environment Using Non-Dominated Sorting Genetic Algorithm

2021 ◽  
pp. 773-789
Author(s):  
Oshin Sharma ◽  
Hemraj Saini
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Data Centers ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Vm Placement ◽  
Energy Consumption Reduction ◽  
Consumption Reduction ◽  
The World ◽  
Placement Algorithm

To increase the availability of the resources and simultaneously to reduce the energy consumption of data centers by providing a good level of the service are one of the major challenges in the cloud environment. With the increasing data centers and their size around the world, the focus of the current research is to save the consumption of energy inside data centers. Thus, this article presents an energy-efficient VM placement algorithm for the mapping of virtual machines over physical machines. The idea of the mapping of virtual machines over physical machines is to lessen the count of physical machines used inside the data center. In the proposed algorithm, the problem of VM placement is formulated using a non-dominated sorting genetic algorithm based multi-objective optimization. The objectives are: optimization of the energy consumption, reduction of the level of SLA violation and the minimization of the migration count.

Sign in / Sign up

Export Citation Format

Share Document