Modelos de Previsão Numérica, Entidades, Novidades

CptRena

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Gostaria de saber se alguém sabe onde e como posso arranjar um meteograma GFS em formato de texto(semelhante ao apresentado aqui no meteopt para diversos locais de portugal) para uma determinada localização mundial?(ex:Dubai)
Tudo o que encontro são imagens...e preciso de valores numéricos para tratar informaticamente.
Obrigado

Utilize um URI com input de coordenadas Latitude e Longitude e pode obter os dados para onde quiser


http://www.meteopt.com/modelos/meteogramas/gfs.php?lat=99.999999&lon=9.999999&lang=en&type=txt&units=m


Cumprimentos
 

Zapiao

Nimbostratus
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Colegas, em que modelos confiam ? É que voces oferecem 10 modelos no tab "previsao" e fico sem saber qual o melhor/realista/enfim o que se engana menos:D
 

halo

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Porque o americano GFS é um dos principais, tem 4 run's diárias, e sobretudo porque é o único que tem todo o output disponível gratuitamente para todos. O europeu ECMWF é considerado o melhor (por estudos/verificação e não simples opinião), os próprios americanos fazem-lhe muitos elogios e até tem pedido ajuda para melhorar o deles. O UKMO também é bastante respeitado, provavelmente o 2º melhor global. O CMC e NOGAPS são aceitáveis.

Mas todos os modelos são necessários, mesmo sendo uns melhores que outros. As diferenças ou mesmo as "manias" de cada um são positivas. Um meteorologista experiente sabe tirar partido dessas especificidades e comportamentos e conforme a situação tirar partido do que uns e outros dizem.


Não te esqueças também dos modelos de mesoescala como o Hirlam, Aladin, WRF, MM5, etc que também são fundamentais.


Alguns links sobre modelos, história e evolução:

http://en.wikipedia.org/wiki/Numerical_weather_prediction
http://en.wikipedia.org/wiki/Ensemble_forecasting

Olá,
Vejo que o pessoal está bastante documentado acerca de modelos de previsão, ainda assim aconselho a visitarem os produtos de nowcasting da EumeTrain, estes estão acessíveis e até têm cursos de formação gratuitos.

Pelo que percebi, neste Forum, os modelos de previsão do ECMWF não estão acessíveis. Podem-me confirmar? Porque precisava de consultar os modelos de previsão de precipitação para um determinado período.
Obrigada
 

ecobcg

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A NOAA está a prever lançar, no final deste ano, um novo modelo de previsão, mais sofisticado, actualizado de hora a hora para todos os estados dos EUA, e com uma resolução de apenas 3km, ou seja, cada "pixel" do mapa da previsão corresponde a uma pequena área de 30km, ao invés dos actuais 13km usados pelo NOAA.

Supostamente este novo modelo vai conseguir diferenciar trovoadas com rotação de trovoadas sem rotação, conseguirá prever "derechos", e se uma tempestade está a aumentar ou diminuir de intensidade, entre outros aspectos de grande importância.

Este novo modelo está já em testes há 2 anos e com muito bons resultados já obtidos em tempestades recentes.

Parece-me mais um excelente avanço.:thumbsup:

Artigo completo aqui:

NOAA’s Upcoming Weather Forecast Model Zeros In Earlier on Severe Weather
Research behind the High-Resolution Rapid Refresh weather forecast model

When it comes to weather, the more you know and the sooner you know it, the safer and better prepared you can be.

Later this year, NOAA’s National Weather Service will usher into daily operations a sophisticated model called the High-Resolution Rapid Refresh, or HRRR, that will update forecasts hourly over the entire lower 48 United States at extremely sharp resolution using the latest observations from a network of ground and satellite-based sensors, radars and aircraft.

The HRRR provides forecast information at a resolution four times finer than what is currently used in hourly updated NOAA models. This improvement in resolution from 13 to three kilometers is like giving forecasters an aerial photograph in which each pixel represents a neighborhood instead of a city.

“When a typical thunderstorm is about 10 to 20 kilometers across, contains both upward and downward air currents as well as other features that give clues to its potential to create dangerous weather, it’s important to be able to see what’s happening inside the storm,” said Stan Benjamin, a research meteorologist at NOAA’s Earth System Research Lab in Boulder, Colo., who leads the team that developed the HRRR. “It’s a game-changer to go from 13 to three kilometers for model resolution.”


HRRR can differentiate between rotating storms, which are more likely to produce large tornadoes, and non-rotating thunderstorms that are often less dangerous. The HRRR can also predict damaging straight-line windstorms called “derechoes” and provide key timing information about when storm severity is increasing and when it’s decreasing. It can provide a wealth of information to forecasters about other weather hazards such as narrow heavy snow bands found in winter storms and areas of low ceiling and visibility. This information is vital to safer and more economic planning for transportation, including decisions by pilots and air traffic managers trying to maneuver planes around hazardous conditions.
Tested and refined across the country for the past two years, including on a number of severe weather events, the HRRR has demonstrated its effectiveness. On June 29, 2012, the HRRR helped identify a major “derecho” severe wind event as it was forming in Illinois and forecast its rapid sweep through Indiana and Ohio during the day and into the Washington, D.C., area that evening. It was also instrumental in providing the public with early forecasts of the May 31, 2013 tornadoes in Oklahoma and flash flooding that day.

“The HRRR’s higher resolution, advanced physics and enhanced data processing, have made a noticeable improvement in forecasting smaller scale weather,” said Steve Zubrick, the Science and Operations Officer for the National Weather Service Baltimore-Washington Forecast Office. “It’s allowed us to better anticipate evolving weather from wind, fog, precipitation and thunderstorms on time scales less than 12 hours.”
Led by Benjamin, researchers at NOAA’s Earth System Research Lab began developing the HRRR five years ago in response to several important developments: widespread recognition that a higher resolution model would improve severe storm forecasts; rapidly improving computer power required to process weather data at the higher resolution; and improved access to national radar data. Researchers also developed detailed techniques to use observations from radar, commercial aircraft, satellites, weather balloons, and surface stations often near airports to allow the HRRR model to differentiate between various weather situations.

The Earth System Research Lab, Global Systems Division, has worked collaboratively with a robust team to refine the HRRR. Key players on the team are NOAA’s National Weather Service including its National Centers for Environmental Prediction, NOAA’s cooperative institute partners; the Cooperative Institute for Research in Environmental Science at the University of Colorado at Boulder and the Cooperative Institute for Research in the Atmosphere at Colorado State University, Fort Collins, the Federal Aviation Administration, the National Center for Atmospheric Research, and the Department of Energy.

For more information, please contact Monica Allen, director of public affairs @NOAA Research, 301-734-1123 or monica.allen@noaa.gov

High Resolution forecasts Derecho
The High-Resolution Rapid Refresh forecast model was the only NOAA model to capture in advance the June 29, 2012 derecho that struck the Washington, DC region. Shown on the right is a video of the HRRR forecast beginning at 11am Eastern Time that day, made available by NOAA in the early afternoon. On the left is the actual radar of the storm, which shows that the HRRR forecast closely aligned with what occurred. (NOAA)
 
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Mário Barros

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£97m supercomputer makes UK world-leader in weather and climate science
28 October 2014 - A new £97m Met Office supercomputer will cement the UK's position as a world leader in weather and climate prediction.

The weather's volatility has long been a popular British conversation topic - but the Government's plans for a new £97m supercomputer unveiled today will cement the UK's position as a world leader in weather and climate prediction.

This supercomputer will be 13 times more powerful than the current system used by the Met Office and will have 120,000 times more memory than a top-end smartphone.

Enabling forecast updates every hour and the ability to provide very high detail weather information for precise geographical areas, the world-leading High Performance Computer (HPC) will help the UK to predict disruptive weather events such as flooding, strong winds, fog and heavy snowfall more effectively.

The supercomputer's impressive computing power also opens up the potential for higher resolution models, which would have the ability to pinpoint more detail for small scale, high-impact weather. For example applying very high resolution (300m) models could help better determine the risk and timing of fog over airports.

Scientists will also explore the benefits of adapting the resolution to improve UK winter forecasts out to months ahead, and assessing the specific regional impacts of climate change such as floods, droughts and heatwaves.

The supercomputer's sophisticated forecasts are anticipated to deliver £2bn of socio-economic benefits to the UK by enabling better advance preparation and contingency plans to protect peoples' homes and businesses.

Chief Secretary to the Treasury, Danny Alexander, said: "We are a country fascinated by the weather, so it's no surprise that from early barometers to this weather supercomputer, we've always led the way in developing technology to predict the weather.

"This £97m investment is a crucial part of the government's wider drive to make the UK the best place in the world to do science and research. By bringing world-class technology to the south west, we are also boosting regional investment and expertise, creating a stronger economy and fairer society."

Universities, Science and Cities Minister Greg Clark said: "This is an investment that says the UK believes in science, putting us up there with the very best in the world enabled by technology that will make huge strides in weather and climate forecasting.

"I have been eager to make this happen for some time, and I am confident that the supercomputer will make this nation more resilient and better prepared for high impact weather and boost the economy - improving lives up and down the country."

The supercomputer, which will be based at the Met Office and Exeter Science Park, will be able to perform more than 16,000 trillion calculations per second, and at 140 tonnes, will weigh the equivalent of 11 double decker buses.

As one of the most powerful supercomputers in the world when fully installed, it will also be a catalyst for regional growth in the South West, supporting collaboration and partnerships between science, business and academia.

High performance computing is an essential component of everything the Met Office does - from daily forecasts to severe weather warnings, as well as climate change research and domestic and international collaborations.

Met Office Chief Executive Rob Varley said: "We are very excited about this new investment in UK science. It will lead to a step change in weather forecasting and climate prediction and give us the capability to strengthen our collaborations with partners in the South West, UK and around the world.

"The new supercomputer, together with improved observations, science and modelling, will deliver better forecasts and advice to support UK business, the public and government. It will help to make the UK more resilient to high impact weather and other environmental risks."

The first phase of the supercomputer will be operational in September 2015 and the system will reach full capacity in 2017.

 

Vince

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Nestes dias vai ficar disponível uma nova versão do GFS, a anterior actualização já data de Setembro de 2012.

Das principais novidades destaca-se a duplicação da resolução horizontal, que passa dos actuais ~27km para ~13km.
A data prevista pelo NCEP para entrar em linha e descontinuar a anterior era ontem, mas a mudança foi adiada para 7 de Janeiro.

Mas como nestes dias isto está meteorológicamente calmo por Portugal, aproveitamos para implementar já a actualização nos nossos produtos baseados no GFS. Os meteogramas estão a ser migrados desde ontem, nos próximos dias serão as cartas.

Como os recursos são escassos e dado o grande aumento da resolução quer horizontal quer vertical do GFS, não temos capacidade de correr sistemas paralelos de testes pelo que se vão notar nestes dias alguns problemas enquanto decorre a migração, bem como outputs diferentes entre cartas e meteogramas. Pedimos desculpas desde já, depois informamos da finalização do processo.

Subject: Global Forecast Systems (GFS) Update: Effective

December 17, 2014

Effective on or about December 17, 2014, beginning with the 1200
Coordinated Universal Time (UTC) run, the National Centers for
Environmental Prediction (NCEP) will upgrade the GFS Analysis and

Forecast System which includes:

- Changing model components
- Increasing horizontal resolution
- Adding 0.25 degree gridded output
- Adding new product fields
- Changing product naming convention
- Changing product timeliness
- Generating downstream model impacts


1) Model changes to the GFS Global Spectral Model:

- Increase horizontal resolution of the first segment of the
forecast from Eulerian T574 (~27 km) to Semi-Lagrangian T1534
(~13 km), and extend the length of forecast from 192 hours to 240
hours

- Increase horizontal resolution of the second segment of the
forecast from Eulerian T192 (~84 km) to semi-Lagrangian T574 (~35
km), and set forecast time from 240 hours to 384 hours

- Change from Eulerian dynamics to Semi-Lagrangian dynamics,
which uses Hermite interpolation in both vertical and horizontal
directions.

- Use 5 minute daily Real-Time Global (RTG) Sea Surface
Temperature (SST) to replace 1.0 degree Reynolds 7 day SST
analysis

- Initialize ice at small inland lakes in the northern hemisphere
with 4 km Interactive Multi-sensor Snow and Ice Mapping System
(IMS) ice analysis data from the National Ice Center. For large
water bodies, use 5 minute NCEP/MMAB ice analysis data to replace
30 minute ice data

- Use 1982-2012 5 minute SST climatology (replacing 1982-2001 1
degree SST climatology).
- Use 1982-2012 30 minute sea ice concentration climatology
(replacing 1982-2001 1 degree climatology).
- Replace update of model snow depth by direct insertion of AFWA
depth data with a blend of the model first guess depth and the

AFWA depth.
- Use X-number to prepare spectral transform base functions.
X-number is a numerical technique. It uses paired numbers to
represent real number to avoid computational underflow or
overflow that can occur in spectral truncation for wave number
larger than T1000.

- Use divergence damping in the stratosphere to reduce noise

- Add a tracer fixer for maintaining global column ozone mass
- Use the Monte-Carlo Independent Column Approximation (McICA)
for Rapid Radiative Transfer Model (RRTM) Radiation

- Reduce drag coefficient at high wind speeds- Use Hybrid Eddy-Diffusivity Mass-Flux Planetary Boundary Layer

(EDMF PBL) scheme and Turbulent Kinetic Energy (TKE) dissipative
heating

- Retune ice and water cloud conversion rates, orographic
gravity-wave forcing and mountain block; and reduce background
diffusion of momentum- Add stationary convective gravity wave drag

- Modify initialization of forecast state variables to reduce a
sharp decrease in cloud water in the first model time step

- Correct a bug in the condensation calculation after the digital
filter is applied

- Replace 1.0 degree bucket soil moisture climatology with
CFS/Global Land Data Assimilation System (GLDAS) climatology at
T574 (~27 km)

- Replace 1.0 degree momentum roughness length climatology by
using a look-up table based on vegetation type

- Add a dependence of the ratio of the thermal and momentum
roughness on vegetation type


2) Model changes to the GDAS/GFS Hybrid 3D-VAR Ensemble Kalman
Filter (EnKF) Data Assimilation:

- Increase EnKF resolution from T254L64 to T574L64

- Assimilate hourly GOES and EUMETSAT atmospheric motion vectors

- Update radiance assimilation:

- Assimilate SSM/IS UPP LAS and Metop-B IASI radiances

- Use enhanced radiance bias correction scheme

- Update to version 2.1.3 of the Community Radiative Transfer
Model (CRTM). CRTM v2.1.3 improves specification of microwave
sea surface emissivities. This, in turn, improves the analysis of
near surface temperature over water, especially in the southern
oceans.

- Use stochastic physics in EnKF ensemble forecasts

- The dump window for GOES Satellite Wind (satwnd) data will
change from 1 hour to 6 hours. Subtypes will be added for
(NOAA/METOP AVHRR SATWIND) infrared cloud motion vector and
(NESDIS/GOES 3.9 micron channel) derived cloud motion vector
 

Vince

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Continental divide

IT WAS far too small a victory to count as an equaliser. But cheers were still heard in American meteorological circles after the storm that hit the country’s east coast last month left the city of New York mostly unscathed. For more than two decades the Global Forecast System (GFS), the leading weather-prediction model produced in the United States, has been notably less accurate than its chief competitor, published by the European Centre for Medium-Range Weather Forecasts (ECMWF). Although this deficit went largely unnoticed for years, it was laid bare by Hurricane Sandy. A week before that storm’s landfall in 2012, the ECMWF predicted it would veer towards the coast while the GFS showed it remaining at sea.

In response to this failure, America’s Congress authorised $34m of extra money to spend on forecasting. A new version of the GFS went into operation on January 14th, and two weeks later it passed with flying colours. On January 25th the ECMWF predicted that New York would, on the 27th, labour under 64cm (25 inches) of snow brought by the storm pictured above. The GFS suggested 18cm. That turned out to be far closer to the truth.

It is, however, too early for the Americans to celebrate. The GFS projection for the blizzard’s western edge differed from the ECMWF’s by 200km (120 miles)—a weather-forecasting hairs’-breadth. The only reason anyone noticed this discrepancy was that the gap happened to encompass the country’s most populous city.

This episode, moreover, may have been a fluke. During its three weeks of operation, the new GFS remained outclassed. On a standard measure—predicting the altitude at which the atmospheric pressure is half as great as at sea level—it still trails the ECMWF model.

Nonetheless, the GFS’s strong showing during January’s nor’easter offers solace to critics who feared America would never catch up with Europe in matters meteorological. Weather forecasting is fiendishly complex, and improvements tend to arise not from great leaps forward but rather an accumulation of incremental advances.

The ECMWF’s most obvious advantage has been in raw computing power. Its Cray XC30 supercomputer can perform up to 2 quadrillion calculations a second, about ten times more than the GFS hardware before the recent upgrade. As a result, it carves up the Earth’s atmosphere into svelte cells 16km square and 137 layers deep, compared with a bulky 27km and a mere 64 layers for the old GFS. The ECMWF’s computing muscle also lets it start its projections with a replay of the past 12 hours of weather, using 40m data points derived from observations collected by ground stations, aeroplanes, balloons and satellites. In contrast, the GFS begins with a snapshot of a single moment.

The ECMWF also deserves credit for deploying its computational force wisely. The centre was a pioneer in using satellites to fill gaps in the data over the oceans, and in developing “ensemble forecasts” that generate a range of outcomes by employing slightly different starting conditions to produce multiple predictions. Its current model runs 52 such forecasts in parallel, each with a probability assigned to it.

Weather forecasters in America have full access to the ECMWF’s model. However, the United States still has good reason not to free-ride on the Europeans’ work. Private American firms have to pay for it, and the ECMWF is unlikely to develop regional or local models focused specifically on America. Moreover, giving the ECMWF a worthy competitor would probably lead to better forecasts overall.

The new GFS has certainly narrowed the gap. Its resolution is now 13km, though it still has only 64 layers. By November it is expected to run on a faster computer than the ECMWF’s. It could be in line for further upgrades if the new, Republican Congress reintroduces the Weather Forecasting Improvement Act proposed last year—though the party’s global-warming sceptics are likely to demand that much of the additional $120m a year the bill offered be taken away from research on climate change.

According to Cliff Mass, a professor of meteorology at the University of Washington, more money will not be enough to catch up with the Europeans. America, he says, must integrate its separate research and forecasting divisions, and include more contributions from non-government experts. Compared with pushing through cultural change in large public bureaucracies, predicting the weather is easy.

http://www.economist.com/news/scien...talk-about-weather-more-americans-do-they-are
 

Knyght

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Vince

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A AEMET está a instalar um novo supercomputador Atos/Bull para correr modelos que encomendou o ano passado por 3,48 milhões €. Com mais de 8000 cores e capaz de 168 teraflops, é 75 vezes mais potente que o Cray que usam actualmente
Ontem chegou o sistema de refrigeração :D

CAIr58j.jpg
6WvXLXm.jpg
 

Vince

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Um leitura muito interessante sobre a boa evolução dos modelos nos últimos anos no que se refere a ciclones tropicais. Embora focado nessa área tropical também aborda alguns pormenores sobre actualizações recentes de modelos que usamos todos os dias, o modo como o NHC usa multi-modelos e multi-ensembles nas previsões, etc.

What's New in Tropical Cyclone Modeling? An Update from the Trenches
With each passing year, forecasters have ever-more-accurate numerical guidance on where tropical storms and hurricanes are most likely to track and how strong they’ll get. Several of the leading models have undergone noteworthy improvements over the past year. Track models have gotten steadily better over the last couple of decades, whereas improvements in forecasting intensity have been much more difficult to come by (see Figures 1 and 2 below), so a great deal of energy has been focused on the latter. Below is a summary of what’s new and cool, based on interviews and email exchanges with the following experts:



--Richard Pasch, Senior Hurricane Specialist, NOAA National Hurricane Center (NHC)

--David Richardson, Head of Evaluation, Forecast Department, European Center for Medium-Range Weather Forecasts (ECMWF)

--Julian Heming, Tropical Cyclone Specialist, UK Met Office (UKMET)

....
http://www.wunderground.com/blog/JeffMasters/comment.html?entrynum=3072
 

Orion

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The forecasting power of top U.S. weather supercomputers will leap tenfold this year thanks to a $45 million upgrade that should put it near the head of the class alongside the rival European system, the National Oceanic and Atmospheric Administration (NOAA) announced Monday.

"NOAA is making the next major investment in computing supercomputer," NOAA chief Katherine Sullivan, the agency's chief, told the annual meeting of the American Meteorological Society.

The top U.S. computer model, the Global Forecast System (GFS) has been in a weather computing "arms race" of sorts with the European Centre for Medium-range Weather Forecasting (ECMWF) model in recent years.

The stark difference in the two models was underscored most dramatically in 2012 when the GFS forecast showed powerful Hurricane Sandy spinning harmlessly out to sea while the European model -- correctly, as it turned out -- showed it making a direct hit on the East Coast.

...

Even without the upgrade, preliminary data shows U.S. computer models beat the European forecasts in 2014, according to NOAA spokesman Chris Vaccaro.

http://www.usatoday.com/story/weath...ather-service-computers-supercharge/21289731/

-------------------

Today, NOAA announced the next phase in the agency’s efforts to increase supercomputing capacity to provide more timely, accurate, reliable, and detailed forecasts. By October 2015, the capacity of each of NOAA’s two operational supercomputers will jump to 2.5 petaflops, for a total of 5 petaflops – a nearly tenfold increase from the current capacity.

...

Ahead of this upgrade, each of the two operational supercomputers will first more than triple their current capacity later this month (to at least 0.776 petaflops for a total capacity of 1.552 petaflops). With this larger capacity, NOAA’s National Weather Service in January will begin running an upgraded version of the Global Forecast System (GFS) with greater resolution that extends further out in time – the new GFS will increase resolution from 27km to 13km out to 10 days and 55km to 33km for 11 to 16 days. In addition, the Global Ensemble Forecast System (GEFS) will be upgraded by increasing the number of vertical levels from 42 to 64 and increasing the horizontal resolution from 55km to 27km out to eight days and 70km to 33km from days nine to 16.

http://www.noaanews.noaa.gov/stories2015/20150105_supercomputer.html
 
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Vince

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Even without the upgrade, preliminary data shows U.S. computer models beat the European forecasts in 2014, according to NOAA spokesman Chris Vaccaro.

O GFS melhorou e aproximou-se mais um pouco do ECM e UKM mas a afirmação não corresponde à verdade em termos gerais/globais, pode é em certos pormenores ser melhor.
De qualquer forma só temos a ganhar com esta "rivalidade", até era um pouco estranho os EUA não terem sequer supercomputadores para correr o GFS ao nível dos que existem na Europa no ECMWF e MetOffice. Eles tem os recursos distribuídos por muito mais entidades, académicas e científicas, centenas. O ideal era mesmo estalar uma "guerra" nesta área, pena que os russos não queiram saber muito disto :)
E convém não esquecer que o ECMWF é melhor porque ingere e processa mais dados mas também leva bastante mais tempo a acabar o processamento de cada run. E depois esse atraso propaga-se pelos modelos de mesoescala que são inicializados com dados dele. Isso faz com que uma previsão de mesoescala para o próprio dia acabe por só ficar disponível bastante tarde, a meio da manhã, o que é uma desvantagem. E nos modelos de mesoescala parece-me que os americanos estão bastante melhor em knowhow e investigação que a Europa.
 
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Orion

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Esse modelo está na amargura. Foi abandonado pela BBC.

http://www.dailymail.co.uk/news/art...gives-contract-worth-millions-foreigners.html

Vai fazer mossa tendo em conta os salários:

http://www.independent.co.uk/news/u...nuses--just-for-doing-their-job-10432757.html

Por curiosidade, estive a ver. Os russos usam os seus próprios modelos. Prever o tempo para o seu próprio território já deve dar dores de cabeça suficientes. Não devem ter incentivos para internacionalizar o modelo. A versão russa do site deles pode ter uma versão mais expandida mas... a barreira linguística é muito grande, pelo menos para mim:

http://www.newton.ac.uk/seminar/20121022141514409

http://www.meteoinfo.ru/

Já de vez deixo esta notícia. Não tenho a certeza se já o fiz:

http://www.washingtonpost.com/blogs...a-from-china-and-russia-but-congress-says-no/
 
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