Sentences with phrase «observational uncertainty»

Few detection studies have explicitly considered the influence of observational uncertainty on near - surface temperature changes.

We recently published a paper exploring the impact of observational uncertainty on an attribution analysis.

• A full resolution of this issue will require reducing the large observational uncertainties that currently exist.

If the bet is accepted how will you include observational uncertainty?

But the warming was still much higher than natural variability and observational uncertainty combined, leaving human CO2 emissions as the likely culprit.

First, what is and is not considered an extreme event needs an appropriate definition and is confronted with the problem of observational uncertainty.

Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea - ice thickness initialization using statistical predictors available in real time.

To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data.

This study addresses the challenge by undertaking a formal detection and attribution analysis of SCE changes based on several observational datasets with different structural characteristics, in order to account for the substantial observational uncertainty.

So the alarm about «certain» future SLR acceleration is completely overwhelmed by real observational uncertainty.

It also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability.

To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational datasets are used as downscaling target data.

«Although the different estimates of OHCA (ocean heat content anomaly) produce seemingly different estimates of interannual ocean heating rate variability, these differences are all within the range of observational uncertainty.

We need to keep evaluating our models against observational data and this is difficult in the presence of observational uncertainty.

Attribution results therefore go beyond modeling uncertainties and are impacted also on observational uncertainties, and indeed positive attribution can be biased toward well - sampled regions.

But since there are reasonable estimates of the real world GMT, it is a fair enough question to ask why the models have more spread than the observational uncertainty.

Then you say, «But since there are reasonable estimates of the real world GMT, it is a fair enough question to ask why the models have more spread than the observational uncertainty.»

Even worse: to numbers with error estimates, it adds a number without proper error estimate (the observational uncertainty for 1993 - 2003 is included, but who would claim this is an error estimation for future ice flow changes?).

Some observational uncertainty in early 20th - century trend (Sections 9.3.3.2, 9.4.1.4; Figures 9.4, 9.5).»

At regional scales, precipitation is not simulated as well, and the assessment remains difficult owing to observational uncertainties.

Observational uncertainties are likely to be more important for surface temperature changes averaged over small regions (Section 9.4.2) and for analyses of free atmosphere temperature changes (Section 9.4.4).

In addition, owing to observational uncertainties and the presence of internal variability, the observational record against which models are assessed is «imperfect».

To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth - System Models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5) archive, and initial condition ensembles of CanESM2 and other models.

The CRF curves shown in Fig. 7 and Fig. 10 of [Shaviv, 2003] have a CRF maximum near 360 m.y., while that shown in [Shaviv and Veizer, 2003] has a maximum near 320 m.y. [Shaviv, 2003] argues that such a shift of this peak is within the observational uncertainty of the position of the Norma Galactic spiral arm and would «increase the agreement» with climate data.

The observed rate of warming given above is less than half of this simulated rate, and only a few simulations provide warming trends within the range of observational uncertainty.

States that, instead, one has to consider additional factors such as internal variability, the tuning of the model, observational uncertainty, the temporal change in dominant processes or the uncertainty in the forcing

However, the predictive skill of real climate predictions is contaminated by model deficiencies and observational uncertainties (Meehl et al. 2014).

The first paper cited notes (caveating that observational uncertainties are considerable) that models do not match observed changes in subtropical relative humidity or in global precipitation.

«So the best we can hope for is to demonstrate that the model does not violate our theoretical understanding of the system and that it is consistent with the available data within the observational uncertainty.»