[This lengthy, scholarly paper, though understated in style, may offer a major challenge to ‘consensus’ climate theory. -Bob]
By Michael Wallace, Hydrologist – Re-Blogged From http://www.WattsUpWithThat.com
I have offered to write this guest essay to reflect recent talks I’ve presented to water resource professionals on hydroclimatology and Solar cycles. As an academic and hydrologic forecaster, I have followed an energy centric, reproducible data path to quantify correlations between solar cycles and atmospheric moisture patterns. I have anchored my study areas upon subdivisions of the hydrosphere, including the Equatorial Trough (ET) and its relative, the Intertropical Convergence Zone (ITCZ). I have exploited the lags to high correlations that I found to produce what appear to be some of the most accurate climate forecasts known.
In focusing on those objectives, I developed a body of work which initially relied upon linear regression between candidate parameters. As I continued to study that information along with other physical phenomena, I developed a more routine capacity to exercise and test my results to the global energy budget foundation sources in peer reviewed literature. In that testing, I found that I could not reconcile the actual data based magnitude of latent heat identified over our planet with the magnitude attributed to GHGs in the widely relied upon foundational sources. I ultimately developed a concern that the foundational energy budget by Trenberth et. al  does not appear to properly account for the magnitude of the latent heat component.
It may also be that the omitted latent energy can account for any or all of the global energy budget assigned currently to greenhouse gases. My academic research also indicates on many levels, including empiricism, linear regression, and physical equations of state, that Solar forcing is the driver of changes in latent heat concentration. Accordingly it appears that there is no need to invoke the GHG theory to explain any of the heat in the global atmosphere.
Origins of a new conceptual model for solar cycle forcing of the hydrosphere
Through advancing my Ph.D. studies, I have been researching the high lagged correlations between solar cycles, the equatorial trough and hydrologic moisture patterns in high altitude middle latitude catchments. As captured by some of my posts at WUWT over the past several years, and by other reports I have authored, my relevant work also branched out into topics of atmospheric ozone, ocean pH, radiant heat transfer, and cyclonic energy.
I have applied this work towards a number of projection and/or forecasting exercises for moisture and temperature at different domains of the atmosphere and hydrosphere. Many of these have shown better accuracy than prevailing models. Those prevailing models include the charts illustrated by Figure 1. That example from the West Wide Climate Assessment utilizes modern day emissions-based global circulation modeling (GCMs) ensembles with downscaling. Those were applied to a series of predictions of long term behaviors of several streamflow gages in the western US. In this example the Upper Rio Grande Watershed (URGW) is represented by flows through the Otowi Gage near Santa Fe.
Figure 1. a. Western Climate Assessment projections for annual volume past Otowi Gage of the Upper Rio Grande in acre ft. Blue line added by Wallace as an annotation of the observations. source: US Bureau of Reclamation USBR Technical Memorandum No. 86-68210-2016-01 West-Wide Climate Risk Assessments: Hydroclimate Projections. Figure 33
b. The higher and sharper the error curve (red dots), the less accurate is the overall performance of the forecast exercise.
I’ve provided the blue observation overlay, which is the actual historical record for that gage in that figure because the authors did not. Their models could not “bear to compare” against observations. I found it helpful to independently produce an estimate of their errors through the scatterplot in red within that figure. Notably some of their results displayed relative errors over 1,000%. A figure at the end of this post features some of my forecasts for a nearby stream so that the reader can compare the relative skill. For those not familiar with this field of hydrology, those WWCA results are extremely poor by most standards. For example, as crude as they can be, the default auto correlation methods are much more accurate, as I explore in a paper in peer review.
Also the WWCA results are unacceptably opaque, by not disclosing poor accuracy. I was pursuing a possibly better set of ideas by early 2014 myself. My ideas revolved around higher transparency and better accuracy as two intertwined goals. By that time I was engaging in systematic time series analyses of streams of the Southwestern US (SWUS). I was the one of the first researchers to develop explicit quantitative correlation metrics between the Pacific Decadal Oscillation (PDO) and streams such as the Upper Rio Grande Watershed (URGW) in northern New Mexico . This reference was never published in a peer reviewed journal, but it was cited by a Federal agency for some endangered species assessments.
Figures 2 through 4 are examples from work I produced and/or presented that year. Figure 2. demonstrates a strong graphically obvious correlation for a four year moving average between the PDO and the Upper Rio Grande in the southern Rocky Mountains of the SWUS. In those reports I cited prior relevant work as well.
Figure 2. Otowi Gage and PDO Index time series comparisons, 4 year trailing averages. Sources  and 
Figure 3. Correlations of Candidate Causal Parameters to Otowi Stream Flow Gage Record. Covering 3 different moving averages and 4 separate climate