Sentences with phrase «ensemble mean response»

Any finite ensemble can only sample the potential for internal variability and the ultimate ensemble mean response has to integrate over all forms of internal variability.

Not exact matches

[Response: The IPCC report is far more than a single line about the short term ensemble mean trend.

[Response: There are a couple of issues here — first, the number of ensemble members for each model is not the same and since each additional ensemble member is not independent (they have basically the same climatological mean), you have to be very careful with estimating true degrees of freedom.

Also, even though we focus on the ensemble - mean response, the range of model responses is also interesting and important to understand; and the climate model response of large - scale environmental conditions needs to be more explicitly connected to the response of tropical storms.

Millar et al. wrote the confusing sentence: «in the mean CMIP5 response cumulative emissions do not reach 545GtC until after 2020, by which time the CMIP5 ensemble - mean human - induced warming is over 0.3 °C warmer than the central estimate for human - induced warming to 2015».

Recently I have been looking at the climate models collected in the CMIP3 archive which have been analysed and assessed in IPCC and it is very interesting to see how the forced changes — i.e. the changes driven the external factors such as greenhouse gases, tropospheric aerosols, solar forcing and stratospheric volcanic aerosols drive the forced response in the models (which you can see by averaging out several simulations of the same model with the same forcing)-- differ from the internal variability, such as associated with variations of the North Atlantic and the ENSO etc, which you can see by looking at individual realisations of a particular model and how it differs from the ensemble mean.

We can derive the underlying trend related to external forcings from the GCMs — for each model, the underlying trend can be derived from the ensemble mean (averaging over the different phases of ENSO in each simulation), and looking at the spread in the ensemble mean trend across models gives information about the uncertainties in the model response (the «structural» uncertainty) and also about the forcing uncertainty — since models will (in practice) have slightly different realisations of the (uncertain) net forcing (principally related to aerosols).

The ensemble mean statistics from the LENS are very clear in projecting an increase in WES as a response to a warmer mean state.

Observed (manual snow survey) and VIC - reconstructed SWE, which exhibit declines across BC, are projected onto the multimodel ensemble means of the VIC - simulated SWE based on the responses to different forcings using an optimal fingerprinting approach.

In this way, we can obtain the expected range of projected climate trends using the interannual statistics of the observed NAO record in combination with the model's radiatively - forced response (given by the ensemble - mean of the 40 simulations).

This indicates that internal variability will dominate over the forced response for NAO trends over the next 30 years, regardless of whether the forced response is estimated from the ensemble - mean of the CESM - LE or the CMIP5 models.

The temperature trends during the past decades as observed and in the (ensemble mean) model response (Fig. 4) are roughly consistent with each other, which indicates that much of the land warming is a response to the warming of the oceans.

No other of the > 30 single forcing runs display a difference from the mean GMST change of the remainder of the ensemble that is more than a fraction of that applying to LU run 1, and there is no physical reason for a massive ocean anomaly to develop in response to very weak land use change forcing.