AI research over the last couple of years at the University of Tasmania could have been a check on the existing mess with historical temperature reconstructions. Reconstructions that suggest every next year is hotter than the last the world over. Except that Jaco Vlok began with the Australian Bureau of Meteorology’s temperature datasets without first undertaking adequate quality assurance (QA).
Re-Blogged From WUWT
From Penn State University and the “but we guarantee you there’s no predictability limit in climate science” department comes this interesting study.
UNIVERSITY PARK, Pa. — In the future, weather forecasts that provide storm warnings and help us plan our daily lives could come up to five days sooner before reaching the limits of numerical weather prediction, scientists said.
“The obvious question that has been raised from the very beginning of our whole field is, what’s the ultimate limit at which we can predict day-to-day weather in the future,” said Fuqing Zhang, distinguished professor of meteorology and atmospheric science and director of the Center for Advanced Data Assimilation and Predictability Techniques at Penn State. “We believe we have found that limit and on average, that it’s about two weeks.”
By Willis Eschenbach – Re-Blogged From WUWT
I came across an interesting 2014 paper called “The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models“. In it, they make a number of comparisons between observational data and 43 climate models regarding the large-scale energy flows of the planet. Here’s a typical graphic:
Figure 1. ORIGINAL CAPTION: “Fig. 7 Average biases (model—observations) in downward solar radiation at Earth’s surface calculated in 43 CMIP5 models at 760 sites from GEBA. Units Wm−2”. The “CMIP5” is the “Computer Model Intercomparison Project 5”, the fifth iteration of a project which compares the various models and how well they perform.
By Amy Bebbington – Re-Blogged From https://www.ukmodels.co.uk
One of the most desirable aspects of the model industry is the flexible nature. No day is the same moving away from the dull and mundane office hours. Attracted to the photoshoot life, aspiring models yearn for the glamour of the world of the fashion pages. But what is life really like for successful models. What does their day-to-day look like? The reality may be slightly different.
By Bob Tisdale – Re-Blogged From http://www.WattsUpWithThat.com
Figure 1 presents two model-data comparisons for global sea surface temperatures, not anomalies, for the past 30-years. I’ve included a comparison for the global oceans (90S-90N) in the top graph and a comparison for the global oceans, excluding the polar oceans (60S-60N), in the bottom graph. Excluding the polar oceans doesn’t seem to make a significant difference. It’s obvious that global sea surfaces simulated by the GISS climate model were warmer than observed and that the GISS model warming rate is too high over the past 3 decades. The difference between modeled and observed warming rates is approximately 0.07 to 0.08 deg C/decade, more than 60% higher than the observed rate. And in both cases the 30-year average sea surface temperature as simulated by the GISS models is too high by about 0.6 deg C.
Figure 1 – Global Oceans