Yup, Yup, Yup, Gotta Study It Some More

In announcing the House Ways and Means Committee “Hearing on Scientific Objectives for Climate Change Legislation.” Chairman Charles Rangel (D-NY) said:

The development of climate change legislation will be a priority for the Ways and Means Committee during the 111th Congress. The Committee must define the environmental objectives that we hope to achieve with climate change legislation before we can design such legislation. These objectives must be based on science.

Changes are unfolding “in ways that are likely to produce an uneven national map of harms and benefits.” This blog previously relayed a report of computer modeling by some independent experts. Their projections were observed to have a high level of detail. The climate scientists could draw some conclusions with a high confidence level.” Since real data has shown other projected indicators to be underestimated, it would be useful to compare newer predictions with current data.

Well, speaking of science, this blog repeatedly has called for a federal mandate we require all utilities to report total carbon emissions produced. An obvious, unstated corollary, is there would be significant financial penalty for false reporting.

This would be vigorously enforced by the EPA (the former, Business as usual Protection Agency). Stop that guffawing, right now! This is serious Washington Theater.

And, how would the regulators know? By satellite tracking, of course.

“Ah, too bad!”

Yup, after a science team dedicated the past seven years to building and testing instrumentation for OCO (Orbital Carbon Observatory, an acronym that matches the chemical diagram for carbon dioxide: O-C-O) “the first satellite designed exclusively to measure atmospheric carbon dioxide from space failed to reach orbit during this morning’s launch.”

OCO was to be complement to Gosat, the Japanese satellite, which successfully launched on Friday. The instrumentation in Gosat was “designed to measure carbon dioxide and methane emissions with an infrared spectrometer and a cloud and aerosol imager.” The plan was that scientists could cross-check each other’s measurements.”

The 2 orbital observatories shared a common mission: to working with a common ground validation network.

“Well, scrub that mission.”

What, independent verification of the worst carbon emitters?

“No, to understand and protect our home planet.”

One Comment

jcwinnie

Posted 2009-4-7 at 12:42 pm | Permalink

According to the Environmental Leader, the EPA (Environment Protection Agency) has issued new guidelines for environmental models.

EPA uses environmental models to simulate the impact of pollutants and to estimate pollution’s effect on public health and the environment. Environmental models also are used to compare the costs and benefits of alternative policies or procedures.

The new guidance (PDF) provides more transparency about EPA’s process, and how it applies environmental models once an environmental issue has been identified. It was prepared by EPA’s Council for Regulatory Environmental Modeling.

Using white papers, the National Research Council’s Models in Environmental Regulatory Decision Making and peer-reviewed literature, the EPA has identified an approach that accounts for model development, evaluation and application.

According to EPA, the model development and evaluation processes “conform to protocols or standards that help ensure the utility, scientific soundness, and defensibility of the models and their outputs for decision making.” This is to ensure a better understanding of the process for companies whose products or projects are subject to EPA review.

The guidance details EPA’s position on best practices, transparency, corroboration, sensitivity analysis and uncertainty analysis.

EPA says that that model developers and users should:
1. subject their model to credible, objective peer review;
2. assess the quality of the data they use;
3. corroborate their model by evaluating the degree to which it corresponds to the system being modeled;
4. perform sensitivity and uncertainty analyses. According to EPA, sensitivity analysis evaluates the effect of changes in input values or assumptions on a model’s results. Uncertainty analysis investigates the effects of lack of knowledge and other potential sources of error in the model.

After Gutenberg