Sentences with phrase «in model hindcasts»

Not exact matches

«In our study we used satellite data for sea ice and sea surface temperatures to run some coordinated hindcast experiments with five different atmospheric models,» Ogawa says.

Your statement that «Thus it is natural to look at the real world and see whether there is evidence that it behaves in the same way (and it appears to, since model hindcasts of past changes match observations very well)» seems to indicate that you think there will be no changes in ocean circulation or land use trends, nor any subsequent changes in cloud responses thereto or other atmospheric circulation.

Thus it is natural to look at the real world and see whether there is evidence that it behaves in the same way (and it appears to, since model hindcasts of past changes match observations very well).

So all models are first tested in a process called Hindcasting.

An NAO - based linear model is therefore established to predict the NHT, which gives an excellent hindcast for NHT in 1971 - 2011 with the recent flat trend well predicted.

For graph 1, I used all the models with no picking to see which ones did better in the hindcast.

In Florida, unpublished historical surveys (S.J. Epperly personal communication) are consistent with our modeled hindcasts that suggest a population increase from the 1960s through the 1980s.

The resulting model is pretty much used «as is» in hindcast experiments for the 20th Century.

[Response: First off, he is confusing models that include the carbon cycle with those that have been used in hindcasts of the 20th Century and are the basis of the detection and attribution of current climate change.

Part of the uncertainty in the attribution is of course how realistic the «noise» in the models is — and that can be assessed by looking at hindcasts, paleo - climate etc..

in AR4 section 10 I believe there is a chart showing which models use which particular forcings for the 20CEN hindcast.

As we write in the paper: «These two models were designed to describe only the short - term response, but are in good agreement with reconstructed sea level for the past 700 y.» The former means we never used them to compute long - range hindcasts — they are merely shown here for comparison purposes, so that readers can see what difference the additional term in Eq.

I should point out that in the ClimatePrediction models used, the first two of their three phases were hindcast, control phases using pre-industrial CO2 levels.

The model ensemble hindcast tracks the two big dips in the real temps, as it should if the models know about El Chichon and Pinatubo.

Your statement that «Thus it is natural to look at the real world and see whether there is evidence that it behaves in the same way (and it appears to, since model hindcasts of past changes match observations very well)» seems to indicate that you think there will be no changes in ocean circulation or land use trends, nor any subsequent changes in cloud responses thereto or other atmospheric circulation.

This can involve «perfect model» experiments (where you test to see whether you can predict the evolution of a model simulation given only what we know about the real world), or hindcasts (as used by K08), and only where there is demonstrated skill is there any point in making a prediction for the real world.

I don't suppose economic models were designed to hindcast, but, as in climate science, a whole world view was built upon their supposed mathematical and statistical prowess.

The performance of models using a climate sensitivity range of from 1.0 to 5.0 is essentially equal in hindcasting.

Come on, you KNOW the models can hindcast if the right parameters are put in but they are pretty atrocius at forecasting.

This is typically what the models predict / hindcast (GISS Model E): There is no temperature hump in the mid 20th century — so that, like the MWP, is a problem for the modelers.

In the end, one need not know with a high degree of accuracy the intricacies of the climate's variability to show an increased warming trend: 3 Furthermore, there are no models that exist that are able to match recent observed warming without taking rising CO2 levels into account, i.e. if radiative forcings from CO2 aren't taken into account, then models don't match hindcasting.

Climate model simulations confirm that an Ice Age can indeed be started in this way, while simple conceptual models have been used to successfully «hindcast» the onset of past glaciations based on the orbital changes.

In a cross-validation hindcast, the model (PHENOM) is able to explain 63 % of the variance in onset date for grid cells containing at least 50 % mixed and boreal foresIn a cross-validation hindcast, the model (PHENOM) is able to explain 63 % of the variance in onset date for grid cells containing at least 50 % mixed and boreal foresin onset date for grid cells containing at least 50 % mixed and boreal forest.

Is this a case where some of the natural oscillations are (were) not emergent in the modeling results... even in a hindcast situation?

Model outputs do produce specific year - to - year fluctuations — fluctuations that are not hindcasted well (that's the weather, after all)-- but nobody's interested in knowing the exact temperature of any particular year.

«The use of a coupled ocean — atmosphere — sea ice model to hindcast (i.e., historical forecast) recent climate variability is described and illustrated for the cases of the 1976/77 and 1998/99 climate shift events in the Pacific.

Because of the «predictions» of highly flawed and dubious climate models, most of which have a problem in making accurate hindcasts.

Let's say that we are given the results of calculations using the original Lorenz 1963 system and that these represent the data that we're going to use to tune up our model of the data in a hindcast exercise.

They are basically saying the latest updates to the models are coincidentally exactly what is needed to make the models match the most recent data in hindcast.

I am saying that the models ability to correctly hindcast 2 - 3 degrees of freedom is worthless in scientific terms, whether the degrees of freedom have been «taken into account» or not.

Do you understand that models which are sensitive to initial conditions can be made to match in hindcast by modifying the initial conditions?

This fact leads to the situation that the models are usually not as good in forecasting than hindcasting even, when there is an attempt to avoid this bias.

More often, models have been tested by hindcasting — they are forced with a known change starting at a past known climate state, and asked whether they can accurately project the output (e.g., a temperature change resulting from a change in CO2, solar forcing, etc.)?

Meehl and Teng recently showed that when this is done, thereby turning a model projection into a hindcast, the models reproduced the observed trends — accelerated warming in the 1970s and reduced rate of surface warming during the last 15 years — quite well.

As for tone, I stand by my assertion that the general claim that models are validated by matching a test vector of 2 - 3 degrees of freedom in hindcast is scientifically an absolute joke.

The lack of any actual survey, let alone comparison of Callendar's model out of sample with hindcasts of more recent GCMs, as Steve has done, means we owe Nick our gratitude for highlighting the inadequacies of AR4 WG1 in this area.

The second problem is that the models fail the skill test in 2/6 hindcast decades.

This application of the models is made despite their inability to show multi-decadal regional and mesoscale skill in forecasting changes in climate statistics when run in a hindcast mode (e.g., see Pielke 2013, and also Section 13.5).

These models can be (and must be) tested in hindcast runs to assess their level of skill at predicting what actually occurred.

The authors» of the papers that I listed do indeed discuss skill at predicting (in hindcast runs) the ability of multi-decadal climate model runs to simulate the real world observed climate.

I have presented peer reviewed papers that do, in fact, falsify the models even with respect to their ability to predict (in hindcast) the current climate.

Finally, I reiterate my request for you and Jason to present papers that document a skill of the multi-decadal (Type 4) regional climate models to predict (in hindcast) the observed CHANGES in climate statistics over this time period.

As I show in my guest post, the CMIP models not only have not shown skill at predicting (in hindcast) regional changes in climate statistics, but often not even the current average climate!

Roger states that one can not consider climate model predictions (his type 4) at the regional scale when their predictive skill in hindcast mode is not demonstrated.

Even more importantly, unless they can actually be shown to be «plausible», it is not appropriate to present to the impacts community without the disclaimer that they have not shown skill at predicting the climate metrics of interest when the models are run in hindcast.

The weather model used can and has been tested very frequently when applied in its weather forecasting application mode (type 1) and statistics of these in hindcasts (type 2), but are now extended to an application that is to my opinion a blend of type 2 and type 4 forecasts.

However, capturing the phenomena in hindcasts and previous forecasts does not in any way guarantee the ability of the model to capture the phenomena in the future, but it is a necessary condition.

Accuracy must be tested by comparing in hindcast runs of the models their ability to:

One should realize that there is ALWAYS a chance that predictions do not come true, even if the model has shown skill in hindcast studies; 2.

If the models show a lack of skill and need tuning with respect to predicting (in hindcast) even the current climate statistics on multi-decadal time scales (much less than CHANGES in climate statistics), they are not ready to be used as robust projection tools for the coming decades.