Hotcoldwetdry: Study Claims Satellite Measurements Too Low Because Models Run Hotter

See, if the data doesn’t agree with the climate cult computer models, science says you change the models data, right? That’s the way the Scientific Method works, if you put forth a hypothesis, test it, analyze the data, and if the data doesn’t conform to the hypothesis, you change the data, right?

Satellites May Have Underestimated Global Warming in the Lower Atmosphere Over the Last 40 Years

May have. Did they or did they not? Are they “suggesting”? Have them maybe might possibly our cult tells us to question them?

New research by Lawrence Livermore National Laboratory (LLNL) climate scientists and collaborators shows that satellite measurements of the temperature of the troposphere (the lowest region of the atmosphere) may have underestimated global warming over the last 40 years.

The research appears in the Journal of Climate.

The team studied four different properties of tropical climate change. Each property is a ratio between trends in two “complementary” variables. Complementary variables — like tropical temperature and moisture — are expected to show correlated behavior. This correlated behavior is governed by basic, well-understood physical processes.

The first three properties considered by the team involved relationships between tropical temperature and tropical water vapor (WV). WV trends were compared with trends in sea surface temperature (SST), lower tropospheric temperature (TLT) and mid- to upper tropospheric temperature (TMT). The fourth property was the ratio between TMT and SST trends. All four ratios are tightly constrained in climate model simulations, despite model differences in climate sensitivity, external forcings and natural variability. In contrast, each ratio exhibits a large range when calculated with observations. Model trend ratios between WV and temperature were closest to observed ratios when the latter are calculated with datasets exhibiting larger tropical warming of the ocean surface and troposphere.

For the TMT/SST ratio, model-data consistency depended on the combination of observations used to estimate TMT and SST trends. Observational datasets with larger warming of the tropical ocean surface yielded TMT/SST ratios that were in better agreement with model results.

See, it’s not that the models should agree with the data, and, if not, the models should be changed, it’s that the data should agree with the models, and, if not, well, we just need to find new data. Because Science!

“Such comparisons across complementary measurements can shed light on the credibility of different datasets,” according to LLNL’s Stephen Po-Chedley, who contributed to this study. “This work shows that careful intercomparison of different geophysical fields may help us determine historical changes in climate with greater precision.”

If climate model expectations of these relationships between tropical temperature and moisture are realistic, the findings reflect either a systematic low bias in satellite tropospheric temperature trends or an overestimate of the observed atmospheric moistening signal.

So, see, since the datasets of direct observations of actual temperatures and such do not conform with the models, which have shown to be way out of line with the actual data, the data must be wrong. Remember when Dr. Roy Spencer showed that 95% of the models were wrong?

They’ve been changing the data, adjusting it for a long time now, and this is just a more blatant way of saying that the data is wrong, as it doesn’t agree with the preconceived notion that we’re doomed from ‘climate change’.