Sentences with phrase «up forecasting model»

Then, based on the historical data and past trends, scientists build a bottom - up forecasting model.

Not exact matches

«We forecast total shipments of MacBook models will grow 10 - 15 % YoY in 2018 (vs. 0 - 5 % YoY decline for the [notebook] industry), up from 15.5 - 16mn units in 2017,» he said in a reported note.

Model forecast wind gusts are consistent w / Category 4 hurricane up entire Florida peninsula... NWS forecasts have been nearly same.

The call came after Tesla forecast a reduction of capital expenses for the year and said it will turn a profit in the second half of the year as Model 3 production ramps up.

As Paul Krugman has written, the common models used to forecast potential GDP take it for granted that if an economy doesn't bounce back quickly from a recession, it's because something has been fundamentally damaged, rather than because the government offered up an insufficient policy response.

As our model forecasts, despite more than 30 % growth in R&D annually through FY 2017 to $ 13.5 billion (up from $ 1.8 billion in FY 2010) and your updated capital return program, Apple's net cash position (currently the largest of any company in history) will continue to build on the balance sheet.

Our long term model forecast points up.

But by October, Musk said that ramping up production was «manufacturing hell» and that the company's current forecast is for 5,000 Model X vehicles a week by the end of June.

So here's what I think about the election: The forecasts — based on complicated models — found in the APSA's PS by real social scientists — with the exception of the one by the astute James Campbell — are, as usual, too timid in terms of picking up the impending surge....

The so - called «Spaghetti model» from the European Centre for Medium - Range Weather Forecasts shows a northerly path moving up East Coast for Hurricane Irma.

«It's impressive, considering that current state - of - the - art numerical weather models, such as NOA's Global Forecast System, or the European Centre for Medium - Range Weather Forecasts» operational model, are only skillful up to one to two weeks in advance,» says paper co-author Cory Baggett, a postdoctoral researcher in the Barnes and Maloney labs.

But when researchers ran the same model with the usual data from the US forecasting programme, it came up short.

We use different computer forecast models that feed initial conditions — including temperatures, humidity, wind speed and wind direction from around the United States and around the world, from the surface all the way up to the jet stream — into different equations.

A new system can provide up to eight - hour forecasts that are updated hourly based on satellite data and weather models

Comparing five state - of - the - art weather prediction models, researchers found current models can forecast both where and how much rainfall a tropical cyclone will produce up to two days in advance.

The sub-model feeds its results into the main computer model and gives a forecast of where the typhoon's epicentre will be up to five days ahead.

The report, led by PhD student Richard Hall and Professor Edward Hanna from the University of Sheffield's Department of Geography, discovered that up to 35 per cent of this variability may be predictable — a significant advance which may help in the development of seasonal forecasting models.

Meteorologists compare NOAA's models with others from international modeling centers to come up with the forecasts seen on the Web or the evening news.

Dr Dudok de Wit's team at the International Space Science Institute in Bern, and the Coupled Model Intercomparison Project, have been using the datasets identified through the network to describe the Sun's influence on climate from 1850 up to the present day, as well as a forecast up to the year 2300.

«Using simple forecasting models, we showed that thermometer data could be effectively used to predict influenza levels up to two to three weeks into the future.

Professor Bernd Blasius from the University of Oldenburg and one of the researchers involved in the study, said: «Our model combines information such as shipping routes, ship sizes, temperatures and biogeography to come up with local forecasts of invasion probabilities.»

The forecasting model is sensitive to detect dengue outbreaks and non-outbreaks with up to twenty per cent chance of false alarm.

The Cray cost # 8 million, making its use for road forecasting alone an expensive proposition, even though a large - scale project using all the processors could model up to 2 million vehicles.

Decadal forecasting, which began in 2007, uses the same climate models that are normally run to simulate changes across many decades, but only goes up to one decade out.

The model is called Forecasting a CME's Altered Trajectory (ForeCAT), and it predicts how a CME can wind up being deflected.

[Response: People have tried that with actual weather forecasts, but the problem is that there are too many degrees of freedom and so you never end up with a model that is «close enough» to the reality to make it useful.

Their current forecasts — always made with the most up - to - date model — are called the analysis.

Thus the weather forecasting centers started to do «re-analyses» in the 1990s — which involved going back over the older data and running it with the most up - to - date forecasting model.

While there has been warm water building up in the pacific, and this warm water is highly correlated to El Nino, and most of the models suggest there will be an El nino (because of these observations rather than any form of «forecast skill»), that does not mean 2014 will be an El nino.

If let Trenberth know about your forecast, and tell him about how your wishful thinking model works, he may just give up on any hope of a resumption of warming.

As far as skill of these sorts of models go, I've been systematizing the approach of using data only up to year Y (e.g. 1915, 1935, etc.) to determine the parameters of a model and measuring how well it forecasts the future (which of course we know today).

All the models used in the IPCC's vast report last year forecast warming of at least 2C if CO2 doubles (up from a 1.5 C minimum rise in the organisation's 2001 report).

The impact of low shortwave fluxes came out well in two - week forecasts of a semi-empirical break - up model forced with output from a long - range weather forecast (contribution by Petrich and Eicken).

The question of how to use a good model of the past to forecast the future is a very interesting one, since the premises that made the model work well up to the present may shift either gradually or suddenly in a way that renders the prediction very inaccurate.

The extension of meteorological modelling (good for 7 to 10 days) toward regional forecasting (hopefully good for up to 30 days) and applied over interlocking areas of the Earth's surface and stratosphere, would be most useful for humanity in its quest to ameliorate the effects of sudden climate change.

Models can't predict local and regional patterns or seasonal effects, yet modelers add up all the erroneous micro-estimates and claim to produce an accurate macro global forecast.

Currently, ICPAC runs WRF model for medium range weather forecasts, PRECIS model for climate chnage and scenario development; and is in the process of setting up a Regional Spectral Model (RSM) for downscaling seasonal forecmodel for medium range weather forecasts, PRECIS model for climate chnage and scenario development; and is in the process of setting up a Regional Spectral Model (RSM) for downscaling seasonal forecmodel for climate chnage and scenario development; and is in the process of setting up a Regional Spectral Model (RSM) for downscaling seasonal forecModel (RSM) for downscaling seasonal forecasts.

For example, as part of HFIP, a group of researchers set up shop in Boulder, Colo., far from tropical weather systems, where they took advantage of high speed computer resources to duplicate a computer model that the Hurricane Center relies on to make its forecasts.

CAMS has been up and running since the summer of 2015 and combines models and observations to monitor and forecast atmospheric pollution and greenhouse gases.

It is perfectly valid to point out that certain of these predictions are a) typos or made up numbers (take your pick), like the Himalayan glacier vanishing act, b) subject to wide disagreement between models, c) not supported by the data, like Hansen's 1988 model forecast, d) other.

Combining observations with information from ECMWF's global forecast model produces a comprehensive, consistent and up - to - date record of the recent climate, unavoidably also carrying a degree of uncertainty.

The team used the new data to improve a computer model that estimates how much greenhouse gas is produced in permafrost in the long term — and they compiled a first forecast: the permafrost soils of northern Europe, northern Asia and North America, they say, could produce up to one gigaton (one billion tons) of methane, and 37 gigatons of carbon dioxide, by 2100.

Moreover, the warm «Blob» in the North Pacific essentially disappears in model forecasts later this winter, likely a product of numerous storm systems bringing vigorous vertical mixing of the ocean and drawing up cooler water from beneath.

While it's relatively easy to cook up an analysis that matches known data, it is much harder to create a model that accurately forecasts the future.

He then writes» we need climate observations to initialize the models to forecast variations up to decadal time scales».

All climate forecasting models are created by a pretty insular and incestuous climate science community that seems to compete to see who can come up with the most dire forecast.

Hurricane intensity forecasts have lagged behind, but this season, forecasters plan to take advantage of faster, more up - to - date computer models to try to make intensity forecasts more reliable.

Studying the last decade, Rupert Seidii, Mart - Jan Schelhaas, Werner Rammer and Pieter Johannes Verkerk of BOKU (Vienna), Wageningen University and the European Forest Institute in Finland fed the figures into climate model programmes and came up with this forecast of further damage.

I'm not very up on this stuff, but if you'll indulge my dumbness for a moment, the consensus here seems to be saying that something that can never be measured directly is used as a baseline for the scary model forecasts (questionable feedbacks added) that the IPCC has 95 % confidence in?

The response (contained in Paragraph 21) is to get the IPCC to dream up some more scary stories and some more modelled emissions forecasts.