The European Centre for Medium-Range Weather Forecasts (ECMWF) is a cooperative effort of 34 member states to provide global numerical weather forecasts and conduct research. It operates a supercomputer to run forecast models using over 500 million observations daily from satellites and other sources. ECMWF produces 13 million meteorological fields daily totaling over 8 TB and disseminates 77 million weather products daily totaling over 6 TB to member states and other partners. It maintains the largest meteorological archive in the world consisting of over 40 PB of data and serving over 650 daily users retrieving over 100 TB per day.
EMPLOYING MULTI CORE ARCHITECTURE TO OPTIMIZE ON PERFORMANCE, FOR APPROACH IN...IAEME Publication
Cloud detection is an important task in meteorological application. Cloud information is especially important for now-casting purposes [1] and as an input for different satellite based estimation of atmospheric and surface parameters [2 -4]. The solar energy is the principal source of energy in the solar system. Clouds have high reflectance and absorption property which is used to distinguish them with land, water or sea area. There is critical demand to develop application, which can calculate the presence of cloud by using the available satellite image processing data, so that prediction of radiated solar energy can be optimised and energy budget can be predicted more easily.
by the examples of two European research projects JHelioviewer and FLARECAST. Talk given for a Taiwanese delegation at the University of Applied Sciences FHNW, Switzerland.
EMPLOYING MULTI CORE ARCHITECTURE TO OPTIMIZE ON PERFORMANCE, FOR APPROACH IN...IAEME Publication
Cloud detection is an important task in meteorological application. Cloud information is especially important for now-casting purposes [1] and as an input for different satellite based estimation of atmospheric and surface parameters [2 -4]. The solar energy is the principal source of energy in the solar system. Clouds have high reflectance and absorption property which is used to distinguish them with land, water or sea area. There is critical demand to develop application, which can calculate the presence of cloud by using the available satellite image processing data, so that prediction of radiated solar energy can be optimised and energy budget can be predicted more easily.
by the examples of two European research projects JHelioviewer and FLARECAST. Talk given for a Taiwanese delegation at the University of Applied Sciences FHNW, Switzerland.
Overall description of Finnish Meteorological Institute's information management system. The presentation describes how FMI produce and handle data and how machine learning is used in the process.
The Copernicus programme (REGULATION (EU) No 377/2014) is a cornerstone of the European Union´ efforts:
To monitor the Earth, its environment and ecosystems
To ensure its citizens are prepared and protected for crises, security risks and natural or man-made disasters
Copernicus as user driven Programme
Places a world of insight (data and information) about our planet at the disposal of citizens, public authorities and policy makers, scientists, entrepreneurs and businesses on a full, free and open basis
Is a tool for economic development and a driver for the digital economy
How is the climate changing? Climate monitoring based on observations Copernicus ECMWF
"How is the climate changing? Climate monitoring based on observations" presentation prepared by Dick Dee and Adrian Simmons, European Centre for Medium-Range Weather Forecasts (ECMWF) for the Common Future Conference session on Copernicus Climate Change Service: a European answer to Climate Change Challenges held in Paris (France), 09 July 2015.
Presented by Christian Muller at the PERICLES workshop 'From Semantics of Change to Change of Semantics', University of Borås, 19 May 2015.
http://www.hb.se/en/About-UB/Current/Events/Pericles-F2F/Workshop/
Copernicus Atmosphere Monitoring Service - An introductionCopernicus ECMWF
Copernicus Atmosphere Monitoring Service: An introduction by
Vincent-Henri Peuch, Head of Copernicus Atmosphere Monitoring Service provided for the ECMWF Copernicus Services Info Day, Brussels, 2 February 2015.
New features presentation: meteodyn WT 4.8 software - Wind EnergyJean-Claude Meteodyn
New feature of meteodyn WT, CFD software for wind resource assessment and wind park optimisation. Worldwide terrain database, convergence improvements and others improvements.
Toward intelligent health monitoring system for space missionsAboul Ella Hassanien
SRGE Workshop on Intelligent system and Application, 27 Dec. 2017 in the framework of the int. conf of computer science, information systems, and operation research, ISSR, Cairo University
El 29 de febrero y el 1 de marzo de 2016, la Fundación Ramón Areces analizó la relación entre 'Big Data y el cambio climático' en unas jornadas. ¿Puede el Big Data ayudar a reducir el cambio climático? ¿Cómo contribuirá ese análisis masivo de datos a prevenir y gestionar catástrofes naturales? Son solo algunas de las preguntas a las que intentarán responder los ponentes. Las ciencias vinculadas al clima tienen en el Big Data una herramienta muy prometedora para afrontar diferentes fenómenos asociados al cambio climático.
In this deck from the Stanford HPC Conference, Peter Dueben from the European Centre for Medium-Range Weather Forecasts (ECMWF) presents: Machine Learning for Weather Forecasts.
"I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future."
Peter is contributing to the development and optimization of weather and climate models for modern supercomputers. He is focusing on a better understanding of model error and model uncertainty, on the use of reduced numerical precision that is optimised for a given level of model error, on global cloud- resolving simulations with ECMWF's forecast model, and the use of machine learning, and in particular deep learning, to improve the workflow and predictions. Peter has graduated in Physics and wrote his PhD thesis at the Max Planck Institute for Meteorology in Germany. He worked as Postdoc with Tim Palmer at the University of Oxford and has taken up a position as University Research Fellow of the Royal Society at the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2017.
Watch the video: https://youtu.be/ks3fkRj8Iqc
Learn more: https://www.ecmwf.int/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
HYPERWIND Project: global and systemic monitoring of offshore renewable power...Jean-Claude Meteodyn
HyperWind is a project to develop a comprehensive
monitoring system for Offshore and On Shore wind
turbines. Meteodyn is working to develop a methodology for modeling system behavior. http://meteodyn.com
Overall description of Finnish Meteorological Institute's information management system. The presentation describes how FMI produce and handle data and how machine learning is used in the process.
The Copernicus programme (REGULATION (EU) No 377/2014) is a cornerstone of the European Union´ efforts:
To monitor the Earth, its environment and ecosystems
To ensure its citizens are prepared and protected for crises, security risks and natural or man-made disasters
Copernicus as user driven Programme
Places a world of insight (data and information) about our planet at the disposal of citizens, public authorities and policy makers, scientists, entrepreneurs and businesses on a full, free and open basis
Is a tool for economic development and a driver for the digital economy
How is the climate changing? Climate monitoring based on observations Copernicus ECMWF
"How is the climate changing? Climate monitoring based on observations" presentation prepared by Dick Dee and Adrian Simmons, European Centre for Medium-Range Weather Forecasts (ECMWF) for the Common Future Conference session on Copernicus Climate Change Service: a European answer to Climate Change Challenges held in Paris (France), 09 July 2015.
Presented by Christian Muller at the PERICLES workshop 'From Semantics of Change to Change of Semantics', University of Borås, 19 May 2015.
http://www.hb.se/en/About-UB/Current/Events/Pericles-F2F/Workshop/
Copernicus Atmosphere Monitoring Service - An introductionCopernicus ECMWF
Copernicus Atmosphere Monitoring Service: An introduction by
Vincent-Henri Peuch, Head of Copernicus Atmosphere Monitoring Service provided for the ECMWF Copernicus Services Info Day, Brussels, 2 February 2015.
New features presentation: meteodyn WT 4.8 software - Wind EnergyJean-Claude Meteodyn
New feature of meteodyn WT, CFD software for wind resource assessment and wind park optimisation. Worldwide terrain database, convergence improvements and others improvements.
Toward intelligent health monitoring system for space missionsAboul Ella Hassanien
SRGE Workshop on Intelligent system and Application, 27 Dec. 2017 in the framework of the int. conf of computer science, information systems, and operation research, ISSR, Cairo University
El 29 de febrero y el 1 de marzo de 2016, la Fundación Ramón Areces analizó la relación entre 'Big Data y el cambio climático' en unas jornadas. ¿Puede el Big Data ayudar a reducir el cambio climático? ¿Cómo contribuirá ese análisis masivo de datos a prevenir y gestionar catástrofes naturales? Son solo algunas de las preguntas a las que intentarán responder los ponentes. Las ciencias vinculadas al clima tienen en el Big Data una herramienta muy prometedora para afrontar diferentes fenómenos asociados al cambio climático.
In this deck from the Stanford HPC Conference, Peter Dueben from the European Centre for Medium-Range Weather Forecasts (ECMWF) presents: Machine Learning for Weather Forecasts.
"I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future."
Peter is contributing to the development and optimization of weather and climate models for modern supercomputers. He is focusing on a better understanding of model error and model uncertainty, on the use of reduced numerical precision that is optimised for a given level of model error, on global cloud- resolving simulations with ECMWF's forecast model, and the use of machine learning, and in particular deep learning, to improve the workflow and predictions. Peter has graduated in Physics and wrote his PhD thesis at the Max Planck Institute for Meteorology in Germany. He worked as Postdoc with Tim Palmer at the University of Oxford and has taken up a position as University Research Fellow of the Royal Society at the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2017.
Watch the video: https://youtu.be/ks3fkRj8Iqc
Learn more: https://www.ecmwf.int/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
HYPERWIND Project: global and systemic monitoring of offshore renewable power...Jean-Claude Meteodyn
HyperWind is a project to develop a comprehensive
monitoring system for Offshore and On Shore wind
turbines. Meteodyn is working to develop a methodology for modeling system behavior. http://meteodyn.com
Greetings all,
By the end of April 2008, the final meeting of the MERSEA European Project set up in Paris, in the Institut Océanographique.
The aim of the project was to develop a European system for operational monitoring and forecasting on global and regional scales
of the ocean physics, biogeochemistry and ecosystems.
It was surely a challenge to get together many different partners to build the future European operational oceanography of
tomorrow. It was also a challenge for the MERSEA teams to demonstrate their capacity to collect, validate and assimilate remote
sensed and in situ data into ocean circulation models, to interpolate in time and space for uniform coverage, to run nowcasting
(i.e. data synthesis in real-time), forecasting, and hind-casting, and to deliver information products. The project also had to
develop marine applications addressing the needs of both intermediate and end-users, whether institutional or from the private
sector
This Newsletter collects some of the many results obtained during this project. Several aspects are tackled: global and regional
forecasting systems, observations, and applications.
The News is written by the Coordinator of the Project, Yves Desaubies. He draws MERSEA results up.
In a first article, Marie Drévillon et al. present the MERSEA/Mercator-Ocean V2 global ocean analysis and forecasting system. In a
second one, Hervé Roquet et al. describe L3 and L4 high resolution SST products. The next article, written by Bruce Hackett et
al., focuses on Oil spill applications. The article of John Siddorn et al. closes the issue by a description of the development of a
North-East Atlantic tidal NEMO system.
Enjoy your reading!
Development of a Java-based application for environmental remote sensing data...IJECEIAES
Air pollution is one of the most serious problems the world faces today. It is highly necessary to monitor pollutants in real-time to anticipate and reduce damages caused in several fields of activities. Likewise, it is necessary to provide decision makers with useful and updated environmental data. As a solution to a part of the above-mentioned necessities, we developed a Java-based application software to collect, process and visualize several environmental and pollution data, acquired from the Mediterranean Dialog earth Observatory (MDEO) platform [1]. This application will amass data of Morocco area from EUMETSAT satellites, and will decompress, filter and classify the received datasets. Then we will use the processed data to build an interactive environmental real-time map of Morocco. This should help finding out potential correlations between pollutants and emitting sources.
Short-term forecasting is usually classified into two groups: the first approach uses physical model in order to compute the downscaling, whereas the second group relies on statistical learning. We propose a new strategy based on both approaches: a micro-scale CFD model coupled with an artificial neural network correction. Selection of the optimal neural network is achieved through a genetic algorithm. This solution is tested on a real case, which leads to a relative RMSE improvement of 17%.
Climate data can provide a great deal of information about the atmospheric environment that impacts almost all aspects of human endeavour. This module explains the importance of climate data, its storage, security, applications and other aspects, in a nutshell.
Big Data Europe SC6 WS #3: PILOT SC6: CITIZEN BUDGET ON MUNICIPAL LEVEL, Mart...BigData_Europe
Presentation at the Big Data Europe SC6 workshop #3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference: BDE PIlot Societal Challenge 6: CITIZEN BUDGET ON MUNICIPAL LEVEL by Martin Kaltenboeck (Semantic Web Company, SWC).
Big Data Europe SC6 WS #3: Big Data Europe Platform: Apps, challenges, goals ...BigData_Europe
Talk at the Big Data Europe SC6 workshop number 3 taking place on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference: The Big Data Europe Platform: Apps, challenges, goals by Aad Versteden, TenForce.
Big Data Europe SC6 WS 3: Where we are and are going for Big Data in OpenScie...BigData_Europe
Where we are and are going for Big Data in OpenScience
Keynote talk at the Big Data Europe SC6 Workshop on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017: The perspective of European official statistics by Fernando Reis, Task-Force Big Data, European Commission (Eurostat).
Big Data Europe SC6 WS 3: Ron Dekker, Director CESSDA European Open Science A...BigData_Europe
Slides for keynote talk at the Big Data Europe workshop nr 3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference by Ron Dekker, Director CESSDA: European Open Science Agenda: where we are and where we are going?
Big Data Europe: SC6 Workshop 3: The European Research Data Landscape: Opport...BigData_Europe
Slides of the keynote at the 3rd Big Data Europe SC6 Workshop co-located at SEMANTiCS2018 in Amsterdam (NL) on: The European Research Data Landscape: Opportunities for CESSDA by Peter Doorn, Director DANS, Chair, Science Europe W.G. on Research Data. Chair, CESSDA ERIC General Assembly
BDE SC3.3 Workshop - Options for Wind Farm performance assessment and Power f...BigData_Europe
Options for Wind Farm performance assessment and Power forecasting (Mr. A. Kyritsis, ALTSOL/TERNA) at the BigDataEurope Workshop, Amsterdam, Novermber 2017.
Big Data Europe: Workshop 3 SC6 Social Science: THE IMPORTANCE OF METADATA & ...BigData_Europe
Big Data Europe: Workshop 3 SC6 Social Science - 11.09.2017 in Amsterdam, co-located with SEMANTiCS2017 titled: THE IMPORTANCE OF METADATA & BIG DATA IN OPEN SCIENCE. Slides by Ivana Versic (Cessda) and Martin Kaltenböck (SWC)
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
2. role is to address the critical
and most difficult research problems in
medium-range NWP that no one country
could tackle on its own
European cooperation at its best
2EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
3. Global numerical weather forecasts
Composition of the atmosphere:
monitoring and forecasting
Climate re-analysis: monitoring
Supercomputing & data archiving
Education programme
European cooperation at its best:
Deliverables and research
3EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
4. 34 member and co-operating states
270 staff
30 countries
Partnerships around the world …
European with a global reach
4EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
5. Mission-driven science
5EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
What does all this cooperation provide?
First of all it gets our member and co-operating states global numerical weather forecasts
How does that work?
We get observations–now mainly from satellites, which give us the present state, and we use
laws of physics and maths to program on the supercomputer.
What this cooperation also achieves is economy of scale with a supercomputer that is
owned jointly by all our member states, of which 50% are used for research purposes
here, 25% are used to deliver our operational forecasts, and 25% are used by our
member states. Some examples of what our member states use their share of those 25% for
are that the Met Office currently uses it for their regional climate runs; Meteo France runs its
seasonal forecast system, Austria runs its operational model. Generally speaking, I’d say
that NMSs tend to use it as a back up, which has proven to be very helpful, like in the case of
Denmark who facing a major computing issue a couple of years back, had to use our system
to produce their operational forecast.
Our HPC also allows us to host the largest meteorological archive in the world
8. Data Acquisition
8EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
Acquisition
329 Destinations
19 different
countries
Data formats
TAC, BUFR,GRIB
NetCDF, HDF, ASCII
More that 530.000.000
Observations
More 30 Gbytes / per day
9. EumetCast Data Acquisition
9EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
EUTELSAT-10A (DVB-S2)
Basic 50.0 Mbps data rate
Max 77.0 Mbps data rate
2015 (Last quarter) - start of
operational High Volume
service
data file volume ~900
Mbytes
10. Traffic Volume Trends Report
10EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
0
10
20
30
40
50
60
70
80
90
100
Internet LAN RMDCN
2007
2008
2009
2010
2011
2012
2013
2014
11. 11EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
A basic description of our models
OOPS
IFS
Product Generation
Data Storage
Encoding + Caching
Processing
Observations
+ Visualisation
+ Web services
12. 12EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
Major assimilated datasets
Surface
stations
Radiosonde
balloons
Polar,
infrared
Polar,
microwave
Geostationary, IR
Aircraft
Receive 530 million observations
from more that 300 sources daily.
14. ECMWF products
14EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
77 million products
disseminated ever day,
totalling 6 TB.
Interpolate output fields into user
required grids
Product generation is also subject to
a dissemination schedule (time
critical)
Products also served via web
visualisation services
17. MECMWF’s Meteorological Archival and Retrieval System
17EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
A managed archive, not a file system
Users not aware of the location of the data
Retrievals expressed in meteorological terms
Data is kept forever:
Dataset becomes more useful once enough data
has been accumulated
Deleting old data in an exponentially growing
archive is meaningless
Consists of 3 layers:
FDB - cache at the HPC level (~80% hit ratio)
DHS - HDD cache (~80% hit ratio)
HPSS Tape system
18. MECMWF’s Meteorological Archival and Retrieval System
18EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS
Fully distributed (migrated 2012)
15 servers for metadata and data
movers
40 PB primary archive
1 PB of disk cache (2.5%)
110 billion fields in 8.5 million files
200 million objects/65 TB added
daily
7000 registered users
650 daily active users
100 TB retrieved per day, in 1.5
million requests