Sentences with phrase «#maria model trends»

#Maria model trends today are more encouraging for the Carolinas.

[2] Goals of the project include (1) identifying statistical trends in key factors affecting mortality, such as lifestyle and other medical conditions; (2) modeling these trends across time; (3) evaluation of potential future scenarios; and (4) creation of software tools to forecast longevity.

Modeling the trend is like modeling a blob of mayo.

«the best - estimate trend value of 0.123 K / decade, it would still be at the extreme low end of the model trends»

The first cut at the revisions linked above has effectively the same match to the model trends as before (maybe a little better) and so no revisions to the models nor to attribution studies are likely.

While this methodology doesn't eliminate your point that the trends from different periods in the observed record (or from different observed datasets) fall at various locations within our model - derived 95 % confidence range (clearly they do), it does provide justification for using the most recent data to show that sometimes (including currently), the observed trends (which obviously contain natural variability, or, weather noise) push the envelop of model trends (which also contain weather noise).

, but the most likely interpretation, and the one borne out by looking at their Table IIa, is that sigma is calculated as the standard deviation of the model trends.

That uncertainty has to factor into the assessment of whether the model trends were reasonable.

We already know that (regional) monsoon variability on the scales for sub-seasonal to interannual are higher than the projected model trends of future mean monsoon rainfall (I've just seen that Kevin has mentioned this also).

None did so before 2012 though, and we know that the model trends speed up as the ice thins.

-- But if the (negative) influence of aerosols (and volcanic) is overestimated, the modeled trend would be way too high.

Kevin Trenberth is now arguing that the reason observed air temperature trends don't match modeled trends is because of «missing heat» in the oceans.

It can be seen that the model trends over 2000 — 2005 are very similar for both forcing cases, and that the observed trend is substantially greater.

[1] van Oldenborgh GJ, Doblas Reyes FJ, Drijfhout SS, Hawkins E (2013) Reliability of regional climate model trends.

As shown in Table 1 and Section 3.3, the model trends are about twice as large as observations in the LT layer, and about four times as large in the MT layer.

This disagreement between observed trends and model trends would be complete.

What is new in this article is the determination of a very robust estimate of the magnitude of the model trends at each atmospheric layer.

During the most recent 10 - year period (2005 — 2014, rightmost points in the chart), the observed trend is 0.01 °C per decade while the model trend is 0.21 °C per decade.

Comparison of observed trends (colored circles according to legend) with the climate model trends (black circles) for periods from 10 to 64 years in length.

The magnitude of the various models trends was shown to be 2 - 4 times over observation.

Recent weather model trends have increased the chances of the first, shore - hugging scenario.

3.7 % of model trends fall below the observed Hadley trend.

In particular, my foci include modeling trends in the timing of transition seasons, such as spring, and evaluating the influences of Arctic amplification and sea ice variability on midlatitude extreme weather events.

Furthermore, the study found that the index they devised to track the current's strength over time closely matched modeled trends, which lends some confidence to the findings.

There is some discussion of how long it will take before Schmidt might admit that the model trends are too high and how he can «get out in front of it» by coming up with a pre-emptive explanation if things continue to go badly.

This seems to be an even greater blow than the failure of the global temperature to follow the models trend lines projected from the warming from 1970 to 1998.

While Zhang et al. (2007) concluded globally that they had detected an anthropogenic influence on the overall latitudinal patterns of precipitation trends (that is, the climate model trends were of the same sign as the observed trends), in the latitude band that includes the majority of the United States population a mismatch between model projections and precipitation trends was found (Figure 1).

Modeled trends (1958 — 2009) of tree mortality (A and B), growth (C and D), and recruitment (E and F) rates at both stand and species levels.

For trends of length 13, 14, 15, and all lengths greater than 34 years, the observed trend is consistent with the collection of model trends (indicated by green in Figure 1), although it lies pretty far out in the low end of model projections in every case.

In statistics, this means that the observed trend is inconsistent with the collection of model trends.

an analysis of the full suite of CMIP5 historical simulations (augmented for the period 2006 - 2012 by RCP4.5 simulations, Section 9.3.2) reveals that 111 out of 114 realisations show a GMST trend over 1998 - 2012 that is higher than the entire HadCRUT4 trend ensemble... During the 15 - year period beginning in 1998, the ensemble of HadCRUT4 GMST trends lies below almost all model - simulated trends whereas during the 15 - year period ending in 1998, it lies above 93 out of 114 modelled trends.

As a result the most those papers can do is attempt to quantify the effects on measurements such as model TCR and model trends using air temperatures for land and ocean and comparisons with the observed using blended temperatures.

[Page 27] The idea that observational trends should be compared to the extrema of model trends, rather than to the confidence interval around the mean of model trends, is statistically and methodologically incoherent.

Median model trend was 0.241 deg C / decade (less than troposphere) while HadCRUT4 trend was 0.181 deg C / decade (Berkeley 0.163).

Measured evidence obviously IS evidence against modeled trends that re different.

There is tens of trillions of dollars difference in implication between the model trend and the observed trend of GMST.

I particularly like «What models make it in the «best» or in the «worst» category, the agreement or non-agreement of the modeled trends with the observed trend in the El Nino 3.4 region for any specific 15 - year preiod is just by chance.»

Model the trend, preferably by applying some fundamental understanding of the system, or, less satisfactorily, by fitting a suitably parsimonious function.

What models make it in the «best» or in the «worst» category, the agreement or non-agreement of the modeled trends with the observed trend in the El Nino3.4 region for any specific 15 - year period is just by chance.

A few quick reactions: a) The tropical LT and MT model trends have gone up a lot compared to Santer et al (about 0.07 0.05 C per decade it appears).

In data spanning 1979 to 2009 the observed trends are significant in some cases but tend to differ significantly from modeled trends.

Such comparisons are not evidence against model trends»

And the more they talk about it, the more clear it becomes that their modeled trends are nothing like global, average or temperature.

MMH are wrong to make inferences about «the models» and «model trends» plural.

In statistical parlance, this situation means that the observed trend can not be reliably considered to be part of the collection of modeled trends.

For the 23 MMH LT model trends in table 1, I get a mean of 0.243 and stdev of 0.073.

The stated model trends do not match linear trends calculated from the MMH archive.

Statistically speaking, instead of there being a clear inconsistency (i.e., the observed trend value falls outside of the range which encompasses 95 % of all modeled trends) between the observations and the climate mode simulations for lengths ranging generally from 11 to 28 years and a marginal inconsistency (i.e., the observed trend value falls outside of the range which encompasses 90 % of all modeled trends) for most of the other lengths, now the observations track closely the marginal inconsistency line, although trends of length 17, 19, 20, 21 remain clearly inconsistent with the collection of modeled trends.

Note by the way that MMH is ambiguous on the existence of modelling error: on the one hand they estimate separate, different b coefficients for the different models, on the other, estimate their variances from the temporal variations around those individual model trend lines only.

The range that encompasses 90 % (light grey lines) and 95 % (dotted black lines) of climate model trends is also included.