science

Remote Sensing Systems

Remote Sensing Systems is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Remote Sensing Systems rather than just read about it. In short: Remote Sensing Systems (RSS) is a private research company founded in 1974 by Frank Wentz. It processes microwave data from a variety of NASA satellites.

Key takeaways

Remote Sensing Systems belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Remote Sensing Systems to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Remote Sensing Systems from memory before moving on to harder problems.

Reference excerpt

Remote Sensing Systems (RSS) is a private research company founded in 1974 by Frank Wentz. It processes microwave data from a variety of NASA satellites. Most of their research is supported by the Earth Science Enterprise program. The company is based in Santa Rosa, California.

Satellite Temperature Record

RSS is a widely cited source of data on the satellite temperature record. Their data is one source of evidence for global warming. Research by Carl Mears, Matthias Schabel, and Wentz, all of RSS, highlighted errors in the early satellite temperature records compiled by John Christy and Roy Spencer at UAH, which had previously showed no significant temperature trend, bringing the derived satellite data into closer agreement with surface temperature trends, radiosonde data and computer models. The 2011 correction to UAH data is closer to the RSS data, but differences remain, for example, in the Lower Troposphere global average trend since 1979, RSS currently have +0.133K/decade while UAH has 0.140K/decade, while the mid-troposphere difference is even more marked at 0.079K/decade and 0.052K/decade respectively. However, in a recent online YouTube video, Dr. Carl Mears, a senior scientist with the team behind the satellite data, explained how he believes his data set needed correction.

I would have to say that the surface data seems more accurate because several groups analyze it, including some who set out to prove the others wrong, and they all get more or less the same answer.

In June 2017, version 4 of the TLT was released, and this substantially revised the trend from 1979 by 36%, from .135K per decade to .184K per decade. Atmospheric measurements taken by a different satellite measurement technique, the Atmospheric Infrared Sounder on the Aqua satellite launched in 2002, show close agreement with surface data.

References

External links Remote Sensing Systems website

Worked examples

Example 1 — a first encounter with Remote Sensing Systems

Start with the simplest possible case. Write down what Remote Sensing Systems claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Remote Sensing Systems before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Remote Sensing Systems ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Remote Sensing Systems

In research: Remote Sensing Systems appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Remote Sensing Systems in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Remote Sensing Systems is common in secondary-school and first-year university syllabi. It links to neighbouring topics Atmospheric science stubs, Companies based in Santa Rosa, California, Companies based in Sonoma County, California, so understanding it makes those chapters shorter.
In everyday life: Look for Remote Sensing Systems outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Remote Sensing Systems in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Remote Sensing Systems means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Remote Sensing Systems out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Remote Sensing Systems in simple terms?

Remote Sensing Systems (RSS) is a private research company founded in 1974 by Frank Wentz. It processes microwave data from a variety of NASA satellites.

Why does Remote Sensing Systems matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Remote Sensing Systems?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Remote Sensing Systems.