Sentences with phrase «most model scenarios»

Most model scenarios make a big assumption: that rising agricultural productivity and vegetable - based diets will limit the need for new farmland.

In most model scenarios, simply cutting emissions isn't enough.

Not exact matches

In most models the ideal scenario for organizations is to get as many engaged employees as possible.

In terms of lead nurturing; one of the most significant tools to use is buyer scenario modeling.

Newcastle would still be forecast by the model as most likely to win under either of those scenarios, because their shooting frequency is higher.

Then we told the model, given our scenario for 2035, tell us the most economical way to meet the total energy demand of the community.»

The most catastrophic scenario for such planet migration, dubbed the Nice model (after the French city), has been gaining ground of late.

And most models looking at future climate change scenarios did not account for aerosols in the stratosphere.

With four colleagues, Dobson co-authored a new paper, published last week in the journal PLoS One, based on a detailed computer model examining how a worst - case road - development scenario might affect the Serengeti's most iconic migratory grazer, the wildebeest (also known as the gnu).

Integrated assessment models create scenarios for the most cost - effective transition toward a sustainable supply of materials and energy while taking the planetary boundaries into consideration.

The estimated size of and uncertainty in current observed warming rates attributable to human influence thus provides a relatively model - independent estimate of uncertainty in multi-decade projections under most scenarios.

Analysis of simple models and intercomparisons of AOGCM responses to idealised forcing scenarios suggest that, for most scenarios over the coming decades, errors in large - scale temperature projections are likely to increase in proportion to the magnitude of the overall response.

The current limits provide us with a unique opportunity to explore the extremely faint fluxes of photons expected in some astrophysical scenarios and they challenge the most recent models of super-heavy dark matter.

For each treatment scenario, the model hosts millions of competitions to simulate how the tumor will most likely progress over time.

These and most other similar large - scale assessments are based primarily on species distribution (bioclimatic envelope) models, which use correlations between species» observed distributions and climate variables to predict their distributions and hence their extinction risk under future climate scenarios [9]--[11].

The cool thing about this collection is it's comprised of in - real - life scenarios — no models or studio pics here — rather personal selfies uploaded most likely various social networks.

Both 911 Targa models exclusively come in an All Wheel Drive version, featuring the wider rear track and body that helps to ensure the optimal distribution of drive power for traction in most road scenarios.

One of the most interesting scenarios raised is that if the government is intent on limiting the capabilities of the agency model, publishers need to figure out what other tools they can use to combat the growing dominance of Amazon.

ln his own financial modeling, ValuePenguin's credit card analyst, Rob Harrow, finds the avalanche method works best to limit interest paid in most scenarios.

Financial planners — not the kind that sell mutual funds, the ones that actually plan finances — can help you model various retirement income scenarios in order to try to determine the most optimal drawdown options.

Across eight rounds, or more if you like, both players will plan out their strategies and then take turns moving their trays of models across the table, either attempting to complete the objectives laid out in the randomly drawn scenario card or just trying to do the most damage.

Analysis of simple models and intercomparisons of AOGCM responses to idealised forcing scenarios suggest that, for most scenarios over the coming decades, errors in large - scale temperature projections are likely to increase in proportion to the magnitude of the overall response.

The estimated size of and uncertainty in current observed warming rates attributable to human influence thus provides a relatively model - independent estimate of uncertainty in multi-decade projections under most scenarios.

As far as I was aware most climate model scenarios include a constant, small, forcing for volcanoes, rather than arbitrary, episodic forcing.

Despite this too - high sensitivity number, the scenario B projection (the only one worth looking at, since that most closely models actual CO2 emissions), was pretty darn good.

Those models proved to be fairly accurate, at least scenario b — which Hansen stated was the most likely at the time he made the predictions.

Models are based on the most recent SRES data and based on A2, A1B and B1 scenarios, which are based on different projections of global growth, development and industrialization.

The test of the model is whether, given the observed changes in forcing, it produces a skillful prediction using the scenario most closely related to the observations — which is B (once you acknowledge the slight overestimate in the forcings).

I am just asking what people think are the most likely scenarios, i.e. which climate model forecasts you think «ahead of time» will prove to be most accurate?

Considering the carbon - cycle feedback, some models (e.g. Cox et al.) estimate large positive vegetation feedback (increased soil respiration, lower photosynthesis due to increased vegetation stress, increased fire frequency...) and some of the most extreme scenarios predict the CO2 concentration to be up to 980 ppm.

Raw climate model results for a business - as - usual scenario indicate that we can expect global temperatures to increase anywhere in the range of 5.8 and 10.6 degrees Fahrenheit (3.2 to 5.9 degrees Celsius) over preindustrial levels by the end of the century — a difference of about a factor of two between the most - and least - severe projections.

Mr Teske is the author of numerous reports, most notably Greenpeace's Energy [R] evolution scenarios, which model how various world regions can shift from a fossil fuel - based energy supply to one based on renewable energy and energy efficiency.

The most common scenario type is based on outputs from climate models and receives most attention in this chapter.

Certainly when testing the short term validity of the model presented in the paper, most people would look to Scenario A for comparisons to actual data.

Close agreement of observed temperature change with simulations for the most realistic climate forcing (scenario B) is accidental, given the large unforced variability in both model and real world.

If you want to calculate how much lower the climate sensitivity model would have to be to match C fine, but that's easier in reference to scenario B given forcings most closely followed that scenario.

In fact, why can't you go one step further and forget about even trying to decide which of the scenarios presented were the most realistic and just dig up the model, plug in the emissions numbers, volcanic eruptions, etc. from the last couple decades and see how well the model holds up.

Even in «low emission» climate scenarios (forecasts that are based on the assumption that future carbon dioxide emissions will increase relatively slowly), models predict precipitation may decline by 20 - 25 percent over most of California, southern Nevada, and Arizona by the end of this century.

This project used a compiled set of emission and forcing scenarios called the Representative Concentration Pathways (RCP) to drive a group of the most complex climate available, so - called Atmosphere Ocean General Circulation Models.

We then projected the current model into the future climate change scenarios and identified winter temperature as the most crucial factor in the model.

«Though most of the CMIP5 models project a nearly ice - free Arctic (sea ice extent less than 1 × 106 km2 for at least 5 consecutive years) at the end of summer by 2100 in the RCP8.5 scenario...»

I recall a scenario (January 2011, IIRC) where all of the models and most of their ensemble members projected what would have been a catastrophic snowstorm for the east coast of the U.S..

Though most of the CMIP5 models project a nearly ice - free Arctic (sea ice extent less than 1 × 106 km2 for at least 5 consecutive years) at the end of summer by 2100 in the RCP8.5 scenario (see Section 12.4.6.1), some show large changes in the near term as well.

Well - fed bears throughout the Arctic have enough fat to see them through a 4 - 5 month fast and even the worst - case scenario models devised suggest that most bears in productive regions like Hudson Bay [and probably, Southern Davis Strait] would survive a 6 month fast.

Mr. Romm does not use any of the emissions scenarios that are the starting point for IPCC climate projections, but instead has developed a forecast for carbon emissions (which are «rising faster than the most pessimistic economic model considered by the IPCC»).

The costs of such scenarios are also significant, but according to most models, the savings in energy costs typically more than exceed the investment costs.

The issue (# 4) of user - defined thresholds is also very important, and addressing issues related to such thresholds (with historical and paleo data and models to create scenarios whereby critical thresholds might be exceeded) can actually be more straightforward than most of what is currently being provided by climate scientists.

One of the most exciting outcomes from Ensembles is the development of a climate mitigation scenario and its analysis by a variety of state - of - the - art climate models, many of which include carbon cycle feedbacks.

Given the existence of many other climate models, one of the most important tests was the comparison of C - ROADS output to the output of disaggregated simulations from the SRES database (e.g., MAGICC) given a range of emissions input scenarios.

Like most climate - economic modelers, the Nature Climate Change researchers use integrated assessment models (IAMs) to generate their scenarios.