Record Snow in Sierra – Near 200% of normal at Boreal Ski resort

Mammoth Mountain hit 600 inches for the first time since records began in 1969 a few days ago. Mainly due to two monster storms, one in December and one in March. Both those months are record-breakers, otherwise the winter is quite normal.

Hoser:

Averaging is what some honest GCM reviews criticize. The models are fundamentally flawed. To paraphrase, they get the right answers for the wrong reasons. They are able to fit observations retrospectively, but have no demonstrated predictive value. They can’t get basic features of PDO or ENSO right. One review warned that the models should not be used by officials to set public policy because of their uncertainty.

The simple fact is that averaging produces better results. Not perfect, better. The models are not fundamentally flawed. If they were fundamentally flawed, then would predict cooler temps as the result of added GHGs. they dont.
The features of PDO and ENSO?
lets see
Contents88.48.4.7
8.4.7 El Niño-Southern Oscillation

During the last decade, there has been steady progress in simulating and predicting ENSO (see Chapters 3 and 9) and the related global variability using AOGCMs (Latif et al., 2001; Davey et al., 2002; AchutaRao and Sperber, 2002). Over the last several years the parametrized physics have become more comprehensive (Gregory et al., 2000; Collins et al., 2001; Kiehl and Gent, 2004), the horizontal and vertical resolutions, particularly in the atmospheric component models, have markedly increased (Guilyardi et al., 2004) and the application of observations in initialising forecasts has become more sophisticated (Alves et al., 2004). These improvements in model formulation have led to a better representation of the spatial pattern of the SST anomalies in the eastern Pacific (AchutaRao and Sperber, 2006). In fact, as an indication of recent model improvements, some IPCC class models are being used for ENSO prediction (Wittenberg et al., 2006). Despite this progress, serious systematic errors in both the simulated mean climate and the natural variability persist. For example, the so-called ‘double ITCZ’ problem noted by Mechoso et al. (1995; see Section 8.3.1) remains a major source of error in simulating the annual cycle in the tropics in most AOGCMs, which ultimately affects the fidelity of the simulated ENSO. Along the equator in the Pacific the models fail to adequately capture the zonal SST gradient, the equatorial cold tongue structure is equatorially confined and extends too far too to the west (Cai et al., 2003), and the simulations typically have thermoclines that are far too diffuse (Davey et al., 2002). Most AOGCMs fail to capture the meridional extent of the anomalies in the eastern Pacific and tend to produce anomalies that extend too far into the western tropical Pacific. Most, but not all, AOGCMs produce ENSO variability that occurs on time scales considerably faster than observed (AchutaRao and Sperber, 2002), although there has been some notable progress in this regard over the last decade (AchutaRao and Sperber, 2006) in that more models are consistent with the observed time scale for ENSO (see Figure 8.13). The models also have difficulty capturing the correct phase locking between the annual cycle and ENSO. Further, some AOGCMs fail to represent the spatial and temporal structure of the El Niño-La Niña asymmetry (Monahan and Dai, 2004). Other weaknesses in the simulated amplitude and structure of ENSO variability are discussed in Davey et al. (2002) and van Oldenborgh et al. (2005).

PDO?

Recent work suggests that the Pacific Decadal Oscillation (PDO, see Chapters 3 and 9) is the North Pacific expression of a near-global ENSO-like pattern of variability called the Inter-decadal Pacific Oscillation or IPO (Power et al., 1999; Deser et al., 2004). The appearance of the IPO as the leading Empirical Orthogonal Function (EOF) of SST in AOGCMs that do not include inter-decadal variability in natural or external forcing indicates that the IPO is an internally generated, natural form of variability. Note, however, that some AOGCMs exhibit an El Niño-like response to global warming (Cubasch et al., 2001) that can take decades to emerge (Cai and Whetton, 2000). Therefore some, though certainly not all, of the variability seen in the IPO and PDO indices might be anthropogenic in origin (Shiogama et al., 2005). The IPO and PDO can be partially understood as the residual of random inter-decadal changes in ENSO activity (e.g., Power et al., 2006), with their spectra reddened (i.e., increasing energy at lower frequencies) by the integrating effect of the upper ocean mixed layer (Newman et al., 2003; Power and Colman, 2006) and the excitation of low frequency off-equatorial Rossby waves (Power and Colman, 2006). Some of the inter-decadal variability in the tropics also has an extratropical origin (e.g., Barnett et al., 1999; Hazeleger et al., 2001) and this might give the IPO a predictable component (Power et al., 2006).
Atmosphere-Ocean General Circulation Models do not seem to have difficulty in simulating IPO-like variability (e.g., Yeh and Kirtman, 2004; Meehl and Hu, 2006), even AOGCMs that are too coarse to properly resolve equatorially trapped waves important for ENSO dynamics. Some studies have provided objective measures of the realism of the modelled decadal variability. For example, Pierce et al. (2000) found that the ENSO-like decadal SST mode in the Pacific Ocean of their AOGCM had a pattern that gave a correlation of 0.56 with its observed counterpart. This compared with a correlation coefficient of 0.79 between the modelled and observed interannual ENSO mode. The reduced agreement on decadal time scales was attributed to lower than observed variability in the North Pacific subpolar gyre, over the southwest Pacific and along the western coast of North America. The latter was attributed to poor resolution of the coastal waveguide in the AOGCM. The importance of properly resolving coastally trapped waves in the context of simulating decadal variability in the Pacific has been raised in a number studies (e.g., Meehl and Hu, 2006). Finally, there has been little work evaluating the amplitude of Pacific decadal variability in AOGCMs. Manabe and Stouffer (1996) showed that the variability has roughly the right magnitude in their AOGCM, but a more detailed investigation using recent AOGCMs with a specific focus on IPO-like variability would be useful.

Smokey. You’ve never stated a proper null hypothesis. Care to give it a try?
The Null for AGW is not what you think it is.

Well, R. Gates, I was thinking you were holding your own fairly well in the discussions, and may actually have some intelligent points, until you wrote, “During this time, CO2 has existed with nice comfortable range, 150 to 280 ppm or so, rising and falling with glacial advances and retreats.”
You clearly do not understand the basic need of CO2 to support life if you think the “nice comfortable range, 150 to 280 ppm” is a GOOD thing. A ‘perfect temperature’ (at least by your standards) doesn’t mean too much if most all life is extinct.
Furthermore, you cherry picked the last 800,000 years wrt CO2 levels, although CO2 levels have been reconstructed for the last several million years. That reconstruction clearly shows that over the last few hundred thousand years there has been an impoverished level of CO2. Moreover, what history – and science – tells us is that the “comfortable range” for life on this planet is around 1000 ppm of CO2.