Spread the love, spread the data!

Posted by on Sep 29, 2009 in Climate Change, Science

Data is to science as to what keys are to a lock. Data allows scientists, those from any discipline who employ the scientific method, to answer questions. Since data can be a valuable tool, it is worthwhile to understand the background related to various types of data. For this example, I will describe climate data and its application to drought monitoring and ultimately famine prevention.

Generally, there are three main types of climate data: remotely sensed, historical reanalysis, and in-situ. Remotely sensed data is generated from sensors that measure information from a secondary source such as a camera or a satellite. This is ideal for collecting data in regions that are not easily accessible such as in the middle of the ocean or in polar environments. In situ data, also known as observational data, is information that is retrieved at a distinct location usually manually derived. Examples of this are weather balloons that can take measurements at a location at various altitudes, qualitative weather descriptions, or data observations such as surface temperature, rainfall, windspeed, etc. Ideally, climate scientists would like to have a continuous data record over an extended period of time (the longer the better) for all points on earth (and even at all vertical dimensions).

Unfortunately, as we know, it is not possible to have observations at all times from everywhere. For one, this would be very expensive and also it is unrealistic in open ocean areas or extreme conditions such as in remote high elevation locations. So, to counteract the course spatial resolution of data observations, some scientists have developed a data set collectively known as reanalysis data that combines both observations with remote sensing and statistically evolves with high skill what certain variables (temperature, wind speeds, humidities, etc.) would be on a globally continuous spatial scale. In a way this solves the issue of limited data, but as we know, directly measured globally continuous data would be a gold mine, albeit totally unrealistic for now…

Now that you have an understanding of the power of data and to some degree observational or in-situ data, we can then understand how valuable that data is. But, what does extra data help climate scientists do? A major project that uses data helps to develop improved climate diagnostics and forecasts related to famine prevention through drought monitoring. Examples of some of these programs are the Famine Early Warning Systems Network (FEWS www.fewsnet.net) and the FAO Global Information Early Warning System (GIEWS www.fao.org/giews/english/index.htm.). These groups both use rainfall, vegetation, and temperature information to research drought periods as well as issue forecasts for potentially unfavorable or famine related conditions.

Everybody agrees that direct or in-situ data has many benefits as long as it is taken in a standard format and methods are standardized throughout the record. A classic example of this is the Keeling Curve that famously depicts the rising CO2 records atop the Mauna Loa observatory in Hawaii providing the first real evidence of increasing greenhouse gas emissions. In that example, the data taken from direct measurements had enormous value years after the first record was taken. But, what happens to all of the observational data that is taken in poor regions where data storage and upkeep is too expensive? And, who uses the data that is hand recorded and how do you relay that data to scientists across the planet? There are numerous regions in the world that have data waiting to be used by climate scientists, but are in a format that is not easily transferred: hand written records spanning in some cases decades. Usually, much of this data is stored in less than ideal conditions; think opposite of a sterile supercomputing facility.

Luckily, there is a group called the International Environmental Data Rescue Organization (IEDRO www.iedro.org) that specializes in recovering and reformatting data from poor regions into a digital format that can then be easily distributed to any interested party for use in various research projects. Their motto is: Saving data, saving lives. Ultimately, this data can then be used by groups such as FEWS and GIEWS to improve their research and applications towards famine prevention and overall food security. This is just one of many uses for rescued data.

Do you suspect that the local river is becoming more polluted over time? If so, start collecting and recording data over time so that you may have the information to either confirm or reject your hypothesis….hmmm, sounds like SCIENCE! Data can be a very valuable tool to help answer some very important questions for yourself and others. Spread the love, spread the data!



  1. Globatron
    September 29, 2009

    Great first post Meteos. I’d love to help. As I’m not the best at recording data, how could others add their skill-set to such a monumental task?

    Also this brings another question up, that if there are gaps in data how can the reports be taken seriously by climate change doubters or deniers such as the scientist in this CBC podcast, Larry Solomon:

    Also what do you think about his thoughts on Michel E. Mann and the hockey stick graph?

  2. Rick Crouthamel
    September 29, 2009

    Thank you for referring to us and the work we do at IEDRO. This was an excellent post, well written and based on a scientific rather than emotional foundation…although we at IEDRO hope it does generate the right kind of emotions and passions. We wish you well.

  3. Akbar Lightning
    September 30, 2009

  4. Father Mapple Moab Adzu III
    September 30, 2009

    his most honorable Meteos,

    the birth of a new contributor, a new force of globatronics is an event of sacred proportions, and so I bless you in your coming globatron experience, and I have sacrificed a cinnabon in your honor. may you find more personal clarity by having this resource for self expression, and may we receive you as a mother does her child. welcome! welcome! welcome!

    this is a great first post, i like that it is not simply about the exoteric topic of the environment, but it also compels us to think about data itself, about the nature of it, about how we relate to information. it is artful, because it asks us to have a relationship with data, a conscious one.

    Meteos, may the gods of globatron help you to find your highest expression. blessings,

    Father Mapple Moab Adzu III

  5. Meteos
    October 1, 2009

    All good data recording begins with a central question mixed in with creativity and organization. Going back to my example in water monitoring one would need to focus first on standardized collection techniques: collect at the same time of the day, at the same place, using the same methods. Don’t collect one day after dinner and then next in the morning. Also, be sure to stick with a standard data collection. Do not use a test bucket to collect samples if in the past you have been using a test tube. Think of things that you can easily record; some of which may not seem related at first. Items to consider would be temperature, bacteria, salinity, number of boat traffic, cloud coverage, etc….

    As for climate projections….that is a very controversial topic that can be data oriented, which could be a future posting. Keep in mind that climate projections are a result of the best available data that we currently have. So, you gotta make due with whatcha got. Is the risk of neglecting whatcha got better than the reward of paying attention to it? That is for us to decide.

    The hockey stick is compelling for many, but not for all. The question is if whether or not this is a trend in periodicity. Perhaps, but have we ever experienced such rapid changes? That may be the stronger argument.



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