By Betsy Youngman. Design by Robert Simmon. May 22, 2009

Spring and early summer are typically rainy in the Midwestern United States. These warm rains that help the early season crops get started, are vital to agriculture, but this spring the rains were well beyond the normal amount. From Wisconsin to Kansas and across to Indiana, deluge after deluge pounded the region. All through the spring season, extreme rain events stacked up like airplanes at a busy airport and this week brought yet another cycle of heavy rains to the already waterlogged farmlands of Central Indiana. This rain pattern, driven by an area of low pressure over the Central Plains combined with high pressure anchored off the Southeast coast of the U.S. to channel moisture up from the Gulf of Mexico into the mid-section of the country.

Map of rainfall in the midwest June 2-12, 2008.
Map of rainfall in the American midwest from June 2-12, 2008. (NASA image courtesy Tropical Rainfall Measuring Mission.)

On the night of June 6, 2008, an intense rainstorm arrived and continued until the early hours of June 7. In the course of one night, Central Indiana received nearly 11 inches (280 mm) of rain, resulting in widespread flooding throughout the region. Many areas were evacuated. On June 8, the Wabash Valley between Lafayette and Terre Haute, Indiana, was placed under flood alert; all residents near the Wabash River were urged to evacuate their homes. On June 9th, President George W. Bush declared 29 counties in central Indiana a major disaster area. In all, the extreme rain event lasted approximately 10 days, caused numerous fatalities and caused $126 million in damages.

Additional articles and images from this time are available on the Earth Observatory.

As a result of better forecasting and flood prediction, the damage and human suffering caused by such floods is now less than it would have been as little as 50 years ago. The advent of modern weather radar and satellite monitoring of precipitation, combined with sophisticated modeling of river flooding patterns, has allowed local officials to be able to prevent large losses of life and property. However, even more accurate predictions are possible as the science and understanding of precipitation patterns continues to improve. Through their contributions of rain gauge data, citizen scientists can play a role in increasing the understanding of precipitation patterns.

The Science

Earth has often been called the “just right” planet. What makes Earth “just right” for life?—our weather and climate. Our unique weather and climate, in other words, temperature combined with the quantity of rainfall and other precipitation, determines where life will flourish or perish on Earth. Too much rainfall, and rivers flood, too little, and soils dry out, making it difficult for plants and animals to survive, resulting in drought and famine.

Water is essential to all life. It comprises 75% of our bodies. We get water from drinking water and from the foods we eat. Water is used for everything. Not only do we use water to grow our crops, it is essential in the manufacturing and transport of our goods and in the processing of our waste. And yet very little fresh water is available for our use. Most of Earth’s water is either too salty (the ocean) or frozen in glaciers.

Additionally, water and precipitation are critical in the redistribution of heat energy around the globe. This movement of water around the Earth is what is known as the water, or hydrological, cycle. Some of the Sun’s energy that reaches the Earth’s surface is used to evaporate and transport the water vapor from one place to another around the Earth. As this water vapor cools it condenses, forming clouds and precipitation.

Throughout history, humans have strived to understand and even control these patterns of weather and climate. By developing an understanding of the patterns of precipitation, scientists are making possible increasingly accurate weather, flood and drought forecasts. In the case of drought, these forecasts allow water managers to decide how to allocate precious water resources. Conversely, in the case of flood events, careful precipitation monitoring and forecasting can improve strategies intended to prevent damage and suffering.

Monitoring Precipitation: How Citizen Scientists Can Help

Scientists use computer models to learn about precipitation patterns and the conditions, both on the land and in the atmosphere, that control them. Models not only allow forecasters to tell you how much rain to expect in tomorrow’s storm, but they also allow scientists to understand how precipitation changes over time.

To check on the models’ accuracy, scientists compare model results to rainfall measurements from ground-based weather stations and satellite measurements. The measurements reveal large- and moderate-scale precipitation patterns such as the anomalies that occur during El Niño or La Niña, when changes in ocean temperatures cause droughts and floods throughout the world.

Models, combined with satellite and ground measurements, have revealed interesting new understandings of precipitation patterns. For example, more rain falls downwind of large cities, and the timing of rainfall can be influenced by weekly commuter cycles. (See Urban Rain, a feature article on the Earth Observatory.

The more information scientists have to both observe patterns and refine the models, the better they understand the processes that control rain. Ground-based measurements provide the most accurate record of rainfall, but ground stations only record rain at a single location, leaving a gap between stations. Since rainfall totals can vary within a small area, these data gaps make it difficult for scientists to learn about the mechanisms that cause small-scale variations in rainfall.

Satellites, on the other hand, provide a “snapshot” of rainfall over a wide area at a given point in time. Satellites don’t have the spatial data gaps that ground stations have, but they do have a time gap—they only see rainfall when they fly over it. Because satellites pass a region only once every 15—30 minutes, precipitation that is light or short-lived is hard to catch accurately. In fact the best rain measuring satellite, which uses radar, passes over every 2-4 hours.

Satellites also have limitations in their monitoring ability over certain geophysical regions. Over land, errors in estimates are generally higher near coastal areas and in regions covered in snow and ice. Precipitation that occurs in relatively shallow clouds, such as ones that occur due to wind flow over hills, valleys and mountains are also likely to have more errors in estimation.

Finally, satellites record the average rainfall in a very wide area—at best, four kilometers across. This means that the satellites can easily miss small patterns such as the influence of local topography (cities, land cover, etc.) on rain.

To compensate for weaknesses in both types of observations, scientists match ground measurements to satellite data and use the relationship between the two to reveal patterns. A large network of ground measurements, such as those collected by citizen scientists, will increase scientists’ ability to understand patterns of rainfall and changes in rainfall.

It’s all a matter of perspective: measuring rain from the ground.

Citizen scientists can contribute much to the understanding of rainfall patterns by reporting precipitation totals at their location. The Community Collaborative Rain, Hail and Snow Network, or CoCoRaHS, collects reports of daily rain, hail and snow events from citizen scientists that are used by a variety of organizations and individuals ranging from the National Weather Service to insurance adjusters and water resources managers. Citizen scientists can join the CoCoRaHs network and contribute data or simply examine the data archives to inquire about local rainfall patterns. CoCoRaHS originated in 1998 at the Colorado Climate Center at Colorado State University. It now has over 12,000 observers in thirty-nine states. (Adapted from What is CoCoRaHS?)

Supplies

  • Rain Gauge: CoCoRaHS Website has a list of suppliers, approximately $20–25
  • Wooden 4" X 4" Post with a beveled top for mounting gauge
  • Tools for placing the post into the ground such as a shovel, drill, screwdriver, hammer, nails/screws and level to attach gauge to post.
  • Detailed map of your location
  • Google Earth (to identify the latitude and longitude of your test site)
  • Data sampling sheet, available in the Tools section of this guide and from idoscience.net, where you can share your observations with other citizen scientists.

Warning

Do not take measurements during a severe storm, flood, or lightning event.

Sampling Procedure

Locate a sampling site

  1. For accurate measurements, your rain gauge should be placed away from any permanent structures such as fences or buildings; 2-5’ above the ground; away from sprinkler systems, dogs and vandals and be easily accessible so that you can check it on a daily basis. You may be able to place the gauge in your yard, but you may wish to identify other locations within your community as well, particularly if you are interested in studying regional variability in rainfall patterns.
  2. Using the map, identify possible rain gauge locations at various places in your region. Choose potential locations that are publicly accessible or where you have permission from the land owner to access the location on a daily basis.
  3. Locate the site(s) in Google Earth. Place the cursor over the sampling site(s) and note the latitude and longitude that appears in the bottom left corner of the Google Earth window. Record this information on the data sampling sheet.
  4. Select a sample location at the site. Look for objects that might adversely affect your collection of precipitation, as outlined in step one. Use the CoCoRaHS training manual pdf for more detailed specifications.
  5. Place the post in the ground with the beveled end on top. Using the level, make sure the post does not lean in one direction or another.
  6. Secure the post to make sure it does not wobble.
  7. Mount your rain gauge on the post, with the gauge top a few inches above the top of the post. Place a level on the gauge to make sure the rain collector is level when you attach it to the post.
  8. On your data sheet, note the condition of your rain gauge. Describe the surroundings (distance from trees and buildings).
  9. If you wish to report your data to the CoCoRaHS network, complete the appropriate paper work to register your location with CoCoRaHS.

Testing Procedure

Use the CoCoRaHS training manual to learn how to read the gauge.

There are a variety of training options on the CoCoRaHS site. From the home page or resources link, one can download additional training slide shows files. Alternately, go to the Indiana page to listen to a web cast of how to use your rain gauge.

Check your rain gauge daily at 7 am (in your local time zone). The hours of 5-9 am (in your local time zone) are acceptable. Record the amount of rain in the gauge on your data sheet and report your rainfall to the CoCoRaHS Website. For more details review the information on the CoCoRaHS Website.

Warning

Do not collect rainfall measurements during a lightning event.

Going Further

Other measurements that may be of interest are hail and snow. These are also described on the CoCoRaHS Website.

How successfully do rain gauges catch rainfall patterns? Do the satellites record the same patterns of data as the ground-based gauges? How many gauges are required in order to observe regional patterns in rainfall? Scientists compare measurements from rain gauges with satellite measurements to answer these and other related questions. By increasing the number of rain gauge measurements, citizen scientists can help increase the overall accuracy and precision of space-based precipitation monitoring. Using the June 2008 Midwest flood event, this section illustrates how to explore satellite data and rain gauge data together to answer questions about regional rainfall.

For this example, we are going to use a station in Monroe County, in south-central Indiana. The station, near Indianapolis, Indiana, received a record-breaking period of rainfall from June 2–12, 2008. This extreme rainfall event subsequently caused intense flooding in the Ohio and Lower Mississippi watersheds.

Part 1. Observer (Ground-based) Data

How to find a station of interest in CoCoRaHS.

Step 1. Access the map of the area that you are interested in.

  1. Launch the CoCoRaHS website

  2. Once the site has loaded, click on the word, “maps”.

    Screenshot of the CoCoRaHS website.
    1. Once the daily maps page loads, select the “Station Number Maps” link from the list of map types. (last one in the list)

    2. Under map location title, use the pull down menu to select “stations,” choose your state of interest. In this case, choose Indiana.

    3. Next choose the “county,” Monroe. Leave the dates and map colors in their default settings.

    4. Click the button, “Get Map”. Screenshot of CoCoRaHS website.

  3. A map window will open with stations shown as little dots with their ID numbers next to them. We will use this station location map for reference later, so save it in the background or on your desktop.

Step 2. Acquire Precipitation data from CoCoRaHS

Screenshot of the CoCoRaHS website.
  1. Open a new window in your browser with the CoCoRaHS home page again.

  2. This time on the top tab bar, click on, “view data”.

  3. A new page will load. On this page there will be a list of station types. Scroll most of the way down the list to the link “List Stations”. This is a list of stations by state and county. Click on this link.

  4. On the next page, choose the state and county you are interested in. For this example choose, Indiana and Monroe County. click search. There are many stations in Indiana, this will select only the 15 stations that are in Monroe County. The stations are listed by; state, county and ID number. In the table of stations, under the “view” heading, click on the magnifying glass in the row with “IN-MN-14” to learn more about this station‘s detailed location, including its latitude and longitude.

  5. Record this station‘s latitude and longitude to use later in the comparison with satellite data. (Record the following: Station IN-MN-14, Latitude 39.265964, Longitude -86.521293.) Optional: click view the station in Google Maps.

  6. On the side bar, under the heading View Data, click on the link “station precip summary.” To access the data from this site.

  7. In the next page that loads, you can type in the station ID numbers of any three stations that are of interest. Use the saved map of stations from step 3 of part 1 to view the station locations.

  8. Type in IN-MN-14, IN-MG-14, and IN-MN-3. Choose the dates 6-02-2008 and 6-12-2008 as your beginning and end dates. Click the “get summary” button.

    Screenshot of the CoCoRaHS website.
    1. You will get a table of data. Check the data to see that it makes sense—is it what you asked for?

    2. Look for any days of intense precipitation. In this case, there was a rainy period from approximately June 1 -15, 2008. What date did the rainfall amount peak? How do the stations vary?

  9. Once you have checked the data, copy and paste the station‘s data from the CoCoRaHS site into a spreadsheet program such as excel.

  10. Since satellites report rain rate in millimeters per hour it will be easier to compare results if you use excel to convert the data from inches to millimeters by multiplying the total by 25.4. (1 inch=25.4 mm)

  11. Produce a graph of rainfall rate in millimeters per 24 hours (y axis) versus date (x axis). Save your graph for comparison with the graph of satellite data that you will produce in the part 2.

Part 2: Above and Below

Comparing CoCoRaHS data with NASA Satellite data from the same location and time period. This example uses the 3-hourly TRMM and Other Rainfall Estimate (3B42 V6).

The Tropical Rainfall Measuring Mission (TRMM, pronounced “trim”) satellite is the most accurate rainfall observing satellite to orbit the Earth. It carries a suite of five instruments that, when combined, allow scientists to gather a very detailed three-dimensional view of rainfall patterns. However, these instruments do not directly measure precipitation. Instead they use a combination of active radar and passive measurements to record the energy and water vapor flowing through the atmosphere. This data allows scientist to estimate precipitation patterns on large scales across the Earth. One instrument is “passive,” observing the intensity of radiant energy that the atmosphere, land, and ocean emit into space at microwave frequencies. The other instrument is the first weather radar in space, recording vertical profiles of rain, similar to surface-based radar systems.

Together, these data sets allow scientists to build a 3-D picture of rainfall patterns in space and time. These estimates are calibrated by comparing the results to ground based observations, such as rain gauges and radars, with the satellite data. By increasing the number of rain gauge measurements scientists will be able to increase the overall accuracy and precision of precipitation monitoring.

To complete the comparison of satellite and rain-gauge data, use the dates, and location of your the selected CoCoRaHS stations as a starting point for a comparison of satellite and observer data.

Step 1. Compare time series data from several rain gauges with that from the Satellites.

  1. Open a new window in your browser. Launch the Giovanni TRMM Online Visualization and Analysis System.

  2. When this page loads, you will see a map of the world. Use your cursor to draw a box around your area of interest, Indiana. Note what latitudes and longitudes are automatically input into the boxes below the map. Optional: Try drawing several boxes on the map in order to better understand the latitude and longitude numbers.

  3. Alternately, use the coordinates that you recorded in part 1 step 3, from the Monroe, Indiana CoCoRaHS observers site as a starting point.

  4. They were Station IN-MN-14 Latitude 39.265964, Longitude -86.521293

  5. In Giovanni choose coordinates that will give you a tight box around this area such as: -88 West, 42 North, 37.5 South , -84.5 East.

    Screenshot of the Giovanni Website
  6. Choose “precipitation” as the parameter, set the temporal dates to begin June 2, 2008, and end June 12, 2008, and the visualization as “time series”.

  7. Click the “generate visualization” button at the bottom of the page.

    Screenshot of the Giovanni website.
  8. A new page will appear, showing you the steps the program is executing to generate the results. After a few seconds, when the processing is complete, you will see a graph.

    Note: the graph will show you rain rates as observed by the satellite. A rain rate is a measurement of how hard it was raining. By contrast, your gauge measures rainfall totals, the amount of rain that fell in a 24-hour period. In theory, the rain rate multiplied by 24 should match the 24-hour rainfall total. In practice, however, this is seldom true because rain does not fall at the same rate over 24 hours.

  9. Compare the graph of the satellite data to a graph of the CoCoRaHS data from Stations IN-MN-14 and IN-MG-14 during the same time period. Note that the gauges both recorded a large amount of rain on the same date that the satellites recorded a heavy rainfall rate.

Graph of satellite rainfall data.

Graph of gauge rainfall data.

Step 2. Mapping the Satellite Data.

While rate versus time is one way to analyze data for several gauges, a broader way to look at rainfall rates across a larger area is on a map. In this example you will plot rainfall rates for this time period on a map for the area. The resulting map will help you to understand where the rainfall was the greatest, allowing you to relate this information to other geographic information such as topographic features and urban areas. In this example, we are going use the rain gauge and TOVAS satellite data for the state of Indiana.

  1. Return to the Giovanni TRMM TOVAS site by clicking the back button from your results window.

  2. Use the same coordinates as in the previous example. Choose the time period June 2-12, 2008.

  3. This time change the parameter,setting to generate a map. Choose “Lat-Lon map, time-averaged” as your visualization.

  4. Click the “generate visualization” button.

  5. The computer will generate a map of the precipitation over the area and time that you have specified. This will appear as an image.

    Map of rainfall data measured by satellite.
  6. You can also download this map to view in Google Earth.

    1. Click on the “download results” tab at the top of the page.

    2. Scroll down to the button of the page.

    3. Under the heading “Output Files”, click the radio button next to the KMZ icon to select this option.

    4. Then click the KMZ icon. It will download to your computer and, depending on your settings, launch Google Earth.

Once Google Earth has loaded, the file you will be able to see the precipitation pattern over the region that you selected.

In Google Earth, observe the map of rainfall intensity for the state of Indiana. In Google Earth, add other features such as rivers, roads and cities to your map.

In the summer of 2008 there were major floods in this region. Add the USGS EDNA watersheds layer.

Use the map to predict in which watersheds the floods would have occurred. How might you, as a local weather personality or hydrologist have advised the citizens living this region? Would you have encouraged citizens living downstream of Indianapolis to evacuate? Read more about this flooding event at an online news source such as msnbc or cbs online.

You can broaden your understanding of the event using Giovanni to further analyze the satellite data.

Some other interesting visualizations that can be done in Giovanni:

  • Choose “animation” to see the amount of rain each day for the period linked together in a quick time movie.

  • Choose “Scatter plot” to plot rainfall data versus error to see the relationship between rainfall rate and error. The greater the rate the greater the error.

  • Return to the TRMM site and choose the monthly averages. Choose the “anomaly plot” for the two-year period between January 2007 and December 2008. “Animate” the monthly averages.

Going Further

Other groups also collect precipitation data, which may be used in a comparison with satellite data. These groups include:

If you are interested in studying rainfall patterns in Arizona, you can map gauge data from Rainlog and satellite data in Google Earth. Both Giovanni and Rainlog will allow you to download a Google Earth file. By layering the two files in Google Earth, you can compare rainfall patterns.

Related questions that could be addressed with satellite data:

Supplies for Backyard Research

  • Rain Gauge: CoCoRaHS Website has a list of suppliers, approximately $20–25
  • Wooden 4" X 4" Post with a beveled top for mounting gauge
  • Tools for placing the post into the ground such as a shovel, drill, screwdriver, hammer, nails/screws and level to attach gauge to post.
  • Detailed map of your location
  • Google Earth (to identify the latitude and longitude of your test site)
  • Data sampling sheet, available in the Tools section of this guide and from idoscience.net, where you can share your observations with other citizen scientists.

Additional background information on the tools used can be found on the CoCoRaHS, rainlog.org and GLOBE websites.

Data and Tools for Earth Observation

  • Giovanni TRMM Online Visualization and Analysis System.
    • Giovanni is a Web-based application developed by the GES DISC that provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data.
  • Google Earth.
  • Additional exploration of satellite data can be done in NEO or NASA Earth Observations. NEO was designed to provide access to and simple analysis of satellite imagery in uniform, familiar data formats. NEO is for educators and students, citizen scientists, and informal educators like museums.

Links

Reference

  1. Huffman, G.J., R.F. Adler, D.T. Bolvin, G. Gu, E.J. Nelkin, K.P. Bowman, Y. Hong, E.F. Stocker, D.B. Wolff, 2007: The TRMM Multi-satellite Precipitation Analysis: Quasi-Global, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scale. J. Hydrometeor. 8(1), 38-55.

The power of citizen science is in sharing your observations with others who are making the same observations in other place. The network of measurements provides a larger picture of air quality than any single person could gather alone.

To share your data with others around the country who are making similar observations, go to Volksdata. [http://www.volksdata.com]

Your First Visit

  1. The first time you visit, you will have to register for the site.
  2. Click on “Register For A New Account” link on the right hand side of the page and follow the instructions.
  3. Sign in with your new username and password, and then click on “Join an existing program.”
  4. Join the CARSON program. You can search for CARSON in the second box titled “Search for Projects”. If you search by metatags, type in: Carson.
  5. The CARSON program is divided into smaller projects. Please click on the project in which you plan to participate: air quality, water quality or precipitation. Each section is treated as a separate project to make it easier for data entry. You may join more than one project or section.
  6. Click on “Request Membership in this Project”. You should receive an e-mail indicating your membership acceptance into the project within 24 hours. Please do this for each project/section that you plan to participate in.

To Enter in your Observations

  1. Log in to Volksdata. [http://www.volksdata.com]
  2. Select CARSON (It should appear under Program Name)
  3. Select the chapter and project of CARSON that you are participating in.
  4. Click on New Observation. This will take you to the Data Entry sheet similar to the sheet you used in the field. Please enter in your observations here.
  5. Once you are finished entering your observations, click on “Submit- Done”. Your observations are now apart of the global CARSON data set.
  6. Click on “View Project Data” to view the entire set of observations.

    Note: If you have additional data to enter for another project, please go back to the CARSON program and click on the next project to access the data entry form.