Sentences with phrase «large uncertainties in the forecast»

This is because clouds have more - complex microphysics than the open sky, so even small errors in the models can cascade into large uncertainties in the forecast.

Professor Curry has led debate in the science community about the process of reviewing climate change, including giving testimony before the US house subcommittee on environment this year, remarking on the many large uncertainties in forecasting future climate.

Projecting the future water balance and moisture state of Arctic soils — and thus the ratio of CO2 to CH4 production — contributes the largest uncertainty in forecasting methane emissions from Arctic land surfaces.

Not exact matches

Both studies came to the same basic conclusion: that the risks and uncertainties involved in budget forecasting were simply too large to allow for a high level of forecast accuracy.

But there is uncertainty associated with all the forecasts and some forecasters are trying to estimate the extent of that uncertainty, which in turn can be used to calculate probabilities of particular events (hung parliament, largest party, etc..)

«While there is some uncertainty regarding the size, position and timing of this year's hypoxic zone in the Gulf, the forecast models are in overall agreement that hypoxia will be larger than we have typically seen in recent years.»

As we mentioned briefly, that leads to a «sweet spot» for forecasting of a couple of decades into the future where the initial condition uncertainty dies away, but the uncertainty in the emission scenario is not yet so large as to be dominating.

These forecasts have uncertainty that, in most cases, is larger than the alpha forecast.

In other words, it is possible that the the climate system does exhibit some kind of long - term chaos in some circumstances, but that the forcing is strong enough to wipe out any significant uncertainty due to initial conditions — at least if one is content to forecast statistical quantities such as, for example, decadal mean January temperatures in some suitably large region, or perhaps temperature variances or quartiles taken over a similar perioIn other words, it is possible that the the climate system does exhibit some kind of long - term chaos in some circumstances, but that the forcing is strong enough to wipe out any significant uncertainty due to initial conditions — at least if one is content to forecast statistical quantities such as, for example, decadal mean January temperatures in some suitably large region, or perhaps temperature variances or quartiles taken over a similar perioin some circumstances, but that the forcing is strong enough to wipe out any significant uncertainty due to initial conditions — at least if one is content to forecast statistical quantities such as, for example, decadal mean January temperatures in some suitably large region, or perhaps temperature variances or quartiles taken over a similar perioin some suitably large region, or perhaps temperature variances or quartiles taken over a similar period.

The models don't by any means capture the uncertainty in their forecasts, and their are a large number of other sources of uncertainty in the models used to forecast emissions from concentrations).

For example, a storm embedded in a confluent large - scale flow (i.e. one whose streamlines tend to converge) will generally have less directional track forecast uncertainty, though the timing of the progress of the storm along its track may suffer.

While climate science can effectively inform us about the range of possible consequences of a warming world, there is a large amount of irresolvable uncertainty inherent in climate forecasting.

You have to remember that the 5 year forecast is derived from a large number of individual runs each with slightly different starting conditions matching the range of the observational uncertainty in the real starting conditions.

My experience in working extensively with temperature measurements and temperature forecasting leads me to believe that our best estimates of global temperature anomalies based on surface measurements have a much larger degree of uncertainty than has been implied by most users of these estimates.

well, if it turns out to be useful for weather forecasting and dynamics at that level, perhaps it would prove useful in reducing the rather large uncertainty the GCM have with clouds and aerosols?

As has been amply documented in the IPCC reports and elsewhere, there remains a large number of uncertainties about Earth's past climate, climate dynamics, and forecasts of future climate.

Decadal climate prediction is immature, and uncertainties in future forcings, model responses to forcings, or initialisation shocks could easily cause large errors in forecasts.

This is where differences in data assimilation methodology and implementation create the largest analysis differences or uncertainty — which is related to future forecast error.

As we mentioned briefly, that leads to a «sweet spot» for forecasting of a couple of decades into the future where the initial condition uncertainty dies away, but the uncertainty in the emission scenario is not yet so large as to be dominating.