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Climate Priorities 2019

By:
Edward A. Reid Jr.
Posted On:
Jan 3, 2019 at 5:48 AM
Category
Climate Change

There continue to be four fundamental climate science research priorities:

  • accurate and comprehensive temperature measurements;
  • accurate climate sensitivity determination;
  • accurate feedback magnitude determination; and,
  • a verified, accurate and comprehensive climate model.

The political process struggles to advance in the absence of these fundamentals, spending essential resources on political advocacy efforts rather than on addressing these scientific priorities.

The first research priority, accurate and comprehensive temperature measurements, applies to both near-surface land and sea surface temperature measurements. Accurate temperature measurement facilities for both applications exist, but they are not comprehensively deployed and are not used exclusively as a result.

The US Climate Research Network (CRN) provides accurate near-surface temperature measurements; and, its use of three instruments assures continuous measurement while permitting detection of instrument failure or drift. The measurement sites are located away from infrastructure which could cause Urban Heat Island effects on the measurements. Deployment of similar measuring stations globally would provide comprehensive near-surface temperature data which would not require “adjustment”.

The collection of drifting buoys and the Argo floats provide accurate temperature measurements, though an array of three measuring instruments would provide the same ability to detect instrument failure or drift available with the US CRN. The total number of floats and buoys deployed and their distribution globally is currently inadequate to produce a comprehensive picture of global sea surface temperature.

Establishing an accurate relationship between the land near-surface and the sea surface temperature measurements and the more comprehensive satellite temperature measurements might minimize the number of additional measuring stations required to provide the necessary data.

The second research priority would facilitate replacing the current estimated range of sensitivities used to drive the climate models with a single accurate and verifiable climate sensitivity. The IPCC currently uses a range of equilibrium climate sensitivity of 1.5 – 4.5. However, recent research by several scientists suggests the equilibrium climate sensitivity (ECS) is more likely between 0.5 and 2.0. These lower climate sensitivities would result in significantly smaller increases in global temperatures as the result of a doubling of atmospheric CO2 concentration. However, these lower climate sensitivities are still estimates over a relatively wide range, rather than a definitive number, leaving significant uncertainty regarding potential future temperature increases.

The third research priority would resolve the dispute between the consensed climate science community, which generally argues that feedback is net positive, and researchers analyzing satellite data, who argue that feedbacks are net negative. This is a very significant difference which affects projections of potential future temperature increases.

The fourth research priority would determine whether it is possible to accurately model the climate changes which have already occurred and been documented over the past 30-year climate period. This would require: initializing the model(s) with conditions 30 years previous; using accurate climate sensitivity and climate feedback measurements in the model runs; and, producing an accurate modeled replication of the climate changes in the intervening 30-year period.

The successful achievement of the first three research priorities listed above would make it possible to pursue the fourth priority. However, it is possible that the known unknowns and the unknown unknowns remaining in climate science might make accurate modeling unachievable. Also, even if accurate modeling of the most recent climate period is achieved, there is still no assurance that the successful model has any predictive ability over the longer term.