The Circle of OOI

OOI Tree 2013-06-25

Let’s be honest. This image won’t be winning any design awards. In fact, it’s not much more than a rehash of an example script for Reingold-Tilford Trees, though I did have to delve into some intricacies of d3 and SVG to figure out how to implement line-wraps of all those long names.

But the crude design of this image belies the incredible complexity behind its subject mater, the Ocean Observatories Initiative or OOI.

The OOI is currently constructing a large network of ocean sensors that will be deployed at 6 sites around the Western hemisphere, with “771 instruments on 38 moorings, 12 seafloor instrument packages, and 27 mobile assets.” (Check out the OOI Instrument Tables for all of the details.)

When you take into consideration all of the data products that can be created by each instrument – for example, wherever you measure temperature, salinity and pressure, you can also calculate density and sound velocity – there will soon be several thousand streams of data spewing forth, as construction is completed and arrays are deployed over the next 18 months. In fact, Station Papa was just deployed last month in the Gulf of Alaska, though it will be a while yet before its data is made available to researchers.

The OOI promises to provide an amazing wealth of data for the up-and-coming generation of oceanographers to explore. And it is sure to provide a ripe source of cool new science for the next 25+ years. We better start preparing for the onslaught.

So why did I create this (admittedly, not very pretty) image?

For the past two years, I’ve been working with of a small team of developers on the OOI project to build a suite of tools for undergraduate educators. Developing web applications and data visualization tools is not an easy task on a normal day. But perhaps our biggest challenge on this project has been to wrap our heads around the giant scope of the OOI, both in terms of the complex structure of its network of sensors, and its grand goals to investigate a full swath of science themes, from carbon cycling and ocean acidification to turbulent mixing and sea-floor volcanic processes.

The image above depicts the top four layers of the current design of the system, comprising 7 arrays and their associated sites and sub-sites at each location. The arrays include 2 coastal sites (the Endurance Array off of Oregon and the Pioneer Array in the Mid Atlantic), 4 global high-latitude sites (off the coasts of Argentina, Greenland, Alaska and Chile), and a regional cabled observatory (also off the coast of Oregon).

I could have included more levels of information in this diagram (remember, there are over 750 instruments planned), but with so much data to display and process, sometimes simple is better. In fact, oftentimes that is the case. After all, any good physicist will tell you to think of the cow as a sphere.

Our team is tasked with designing interfaces that will allow teachers and students to easily visualize and analyze OOI data, and creating this image was just one exercise we used to develop our understanding of the full-scale design of the OOI.

You can expect to hear more about the OOI over the next year, and particularly the educational tools we’re working on. And we’ll definitely be looking for your help as we try to make the data and information from the OOI easy to use in educational environments.

Which is why I thought I’d share this image now, to invite you into the circle.

The End of Upwelling

1 week change in Sea Surface Temperature from July 12 to 19, 2013fig_0719_7day_diff_cb

What a difference a week makes.

Late last week, the waters off New Jersey were between 5-15 degrees below normal thanks a persistent pattern of coastal welling in which warmer surface waters were pushed offshore and replaced by colder waters from below.

This year’s upwelling, which typically occurs this time of year, was longer than usual due to a strong Bermuda High. The High also stalled weather fronts along the eastern seaboard, carrying a lot of moisture up the East Coast from the Gulf of Mexico. But it was the upwelling that caused a lot of consternation among beachgoers in New Jersey, particularly on Long Beach Isltand where the upwelling was strongest. (Warning, the comments on that last link are a sad example of the urgent need for scientists to become more involved in communicating science.)

However, this week, the Bermuda High shifted west, causing record high temperatures across much of the East coast and odd rainstorms out west. It also reversed the coastal upwelling pattern enough so that surface waters could return to their seasonal norms.

The image above shows the change in sea surface temperature over the last week, between July 19 and July 12. (Technically, this map shows the difference between two 7-day composites, one ending on the 19th and the other on the 12th.) Almost the entire region warmed up a few degrees thanks to the strong sun and cloudless days we’ve had. But it is the coastal waters off NJ that increased the most, from 5-12 degrees Fahrenheit. The shift in winds allowed warmer waters from offshore to head back towards the coast, while at the coast, previously upwelled cooler waters were subject to downwelling.

For the ocean, and all the fish in it, this is a huge change to cope with in just a few short days. But if you’re at the beach, it means a more pleasant swim is in your future.

Image Note: I created a new colormap for this image that includes 4 color points instead of the traditional 2 for a divergent color scale (e.g. blue to white to red). Let me know what you think!

Satellites vs. Buoys

A little while back, I received the following question from a Visual Ocean visitor, and thought it would be fun to answer it as a post.

When might satellite sst data be more informative than buoy data?

The short answer is: it depends. You know, like all things in science.

Advantage: Satellites
Perhaps the biggest advantage satellites have is the ability to measure Sea Surface Temperature (SST) over large swaths of the ocean, while buoys can only measure temperatures at a single location.

The typical AVHRR sensor orbiting the Earth from 520 miles up can observe an area that’s over 1,500 miles wide with a resolution of 0.68 miles. By contrast, a single buoy can sample only within a single pixel from the satellite’s perspective. To put that into context, in the Mid Atlantic the typical satellite SST pass contains around 600,000 pixels of data, covering an area of over 250,000 square miles (that’s about the size of 35 New Jerseys). Meanwhile, there are only around a dozen buoys in the same area.

So if you want to study large-scale or regional features like fronts and eddies that occur over a large area, you’ll definitely need to use satellite data. In addition, anyone who has ever seen an SST satellite image knows there is a lot of spatial variability out there, so you’ll also need to use satellite data if you want data close to your study area (or beach house) than the nearest buoy, which could be hundreds of miles away.

Advantage: Buoys
On the other hand, buoys can see through clouds. Well, not really, but many satellite sensors can not, which is why you often see large white areas in SST imagery. Worse yet, when a large storm, like a hurricane, happens to move through an area, it can block the view from satellites for several days. And that’s a problem because the most interesting events in the ocean often occur when storms are overhead.

Similarly, many ocean-sensing instruments are placed on polar orbiting satellites, which are not able to measure the same location constantly. There are several satellites in orbit that measure SST, so this generally isn’t a problem as long as you’re okay with 4-10 measurements a day. Other sensors, like those for chlorophyll or salinity, are on fewer satellites, so it may be several days or more between measurements, and even longer if clouds are in the way.

However, a buoy that is sitting in the ocean can take measurements constantly. Every day, every hour, every second, every microsecond or whatever a scientist might need. In general, buoys that measure SST record data every hour, which is often sufficient for most investigations.

So, if you want to study high-resolution and/or local processes, such as those concerning specific habitats or ecosystems, then buoys are your best bet. Likewise, they’re also quite useful if your favorite fishing spot is nearby.

If you have a question about data visualization in oceanography you’d like me to answer, please let me know using the contact form or send a message to @visualocean on Twitter.

The Ocean in Red, White and Blue

Red, white and blue map of SST Gradients in the Mid Atlantic on July 4, 2013

To celebrate Independence Day, I thought it would be fun to dress up the ocean in a little red, white and blue.

If you’re curious, the image above represents the gradient of sea surface temperature (SST) at each point, and is based off of today’s 7-day composite of SST collected by the AVHRR instrument on NOAA’s polar orbiting satellites.

For every point, if the temperature change from its left (or below) neighbor to its right (or above) neighbor increases, then the gradient is considered positive and is colored red. Similarly, if the temperature decreases as you go from left to right or bottom to top, then the gradient is negative and is colored in blue. If the temperature doesn’t change much, white is used. The darkest colors (red or blue) represent a temperature change of around 2-3 degrees Fahrenheit over 2km of distance.

The map above is actually the sum of the horizontal and vertical gradients (i.e. dT/dx + dT/dy), so areas that are blue, indicate areas where colder temperatures can be found towards the Northeast.

In the image, a few patterns stand out, particularly the north wall of the Gulf Stream which shows up as blue streaks, indicating colder temperatures to the North. The waters off New England show up as a dark mess of blue and red, due to the large number of clouds in the area over the past few days, not to mention all the hot weather warming up the cold waters, both of which resulted in uneven measured temperatures, and therefore chaotic calculated gradient values.

Scientists often use a gradient calculations to identify large-scale features in the ocean, like fronts and eddies, which can be seen in the image. However, to do so they generally would calculate the gradient over larger areas than the 1km pixels used above or use a combination of filtering or averaging to smooth out the features and make them stand out more.

Using raw SST data to calculate gradients results in an image that is very noisy. But then, fireworks are noisy too… and they are also quite beautiful to behold.

Happy 4th!

Tropical Storm Andrea clouds up the ocean

False-color image from NOAA-18 at 4:36pm on June 7, 2013

This week, was the start of the 2013 Hurricane Season, and already forecasters have declared the first storm of the season. So with one week down, I’d say we’re on track to meet NOAA’s prediction of an active to extremely active season.

Tropical Storm Andrea started as a small storm system in the in the Gulf of Mexico earlier this week, and by Wednesday evening she had grown (barely) into a low level Tropical storm. Tropical Storm Andrea then made landfall in the Big Bend region of Florida, causing some minor coastal flooding and wind damage in the Tampa area, before heading up the eastern seaboard. For the most part, Andrea was primarily a major rain event, dampening the spirits of many who are anxious for summer to finally arrive.

Large storm systems are also a nuisance to satellite oceanographers, who generally need a clear view of the ocean to measure physical variables like sea surface temperature, or the amount of chlorophyll and sediment in the water.

The image above was generated using data collected by the AVHRR instrument on NOAA-18 as it flew over the area at 4:36pm. AVHRR does not collect data in the visible light range, so this false-color representation was created by converting data from the red and infrared channels on the satellite into an image resembling a true-color photo.

What is clear from this image, is that the sky is not so clear over the ocean. In fact, the only clear areas over water are off the coast of South Carolina and over the Great Lakes, which show up as dark blue. To an oceanographer then, this image doesn’t offer much to look at, but for a meteorologist, it’s a different story.

For more on the aftermath of Tropical Storm Andrea’s deluge, I encourage you to check out the New Jersey CoCoRaHS site tomorrow to see how much rain fell on the state.

Next Generation Activity Development

NGSS Middle School performance expectations for Weather and Climate - page 58
If you’re a science educator, unless you’re a troglodyte (which let’s face it, every department has at least one of), you’ve probably been paying attention to the development of the Next Generation Science Standards or NGSS. The new standards are the culmination of years of work by scientists and educators across the country to rethink the way science is taught (and assessed) at the K-12 level, focusing on the depth of knowledge rather than breadth, while emphasizing an understanding of scientific practices rather than just core content.

Now, if you’re like me, you probably glanced at the draft versions a few times, but never really took the time to truly understand the new standards and the NRC Framework they are built upon. But now that the NGSS is out, for those of us dedicated to supporting K-12 educators with curriculum and professional development, the hard work really begins.

Last week, I had an opportunity to look through the standards alongside many other ocean educators at the National COSEE Network Meeting. Our goal was to figure out how the NGSS could be used to develop activities, or rather, how we need to adjust our activity development process to meet the goals of the new standards (and by extension, the districts and teachers who will follow them). Given how dense the NGSS is, and with only an hour to review and reflect on them, we didn’t get very far. However, I did take away a few key insights:

  • As they’re presented, the top of each page features the “performance expectations” for each topic or theme. These are the new standards, but in general, they are not content specific as many existing standards are.
  • The disciplinary core ideas, found in the middle orange box at the bottom of each page, are more akin to existing content-based standards. If you are going to develop an activity on a particular subject, identifying standards that include a given topic as a core idea might be a good place to start.
  • However an activity should be more than just an elicitation of content, and it’s important to understand how a core idea intersects with a given set of science and engineering practices, included in the blue box in the bottom left. These practices could be incorporated as the approach or methodology students use when carrying out an activity, again placing the emphasis of the activity on the practices of science rather than a hodgepodge of content.
  • To that end, I think the performance expectations are not necessarily the “content” that one might teach towards, but rather they should be used as the activity goal one can use to assess students’ scientific competency in a given area.
  • As the Appendix on Conceptual Shifts explains, the standards are “student performance expectations – NOT curriculum” meaning that the combinations of core ideas, practices and expectations provided should not be thought of as rigidly linked. That said, in these early days, as we think about developing new curriculum to meet these standards they are a good place to start.
  • Similarly, it seems that many districts may use the Topic Arrangement of the NGSS as the basis for structuring their curriculum, and will probably be looking for help at that level.

Personally, I’ve never really been a fan of standards. That is to say, I’ve always disliked how many educators and especially administrators simply use them as an exercise in bean counting.

But I am excited about the new standards because they represent a fundamental shift in thinking away from content to how science is practiced in the real world. Hopefully, as ocean science educators we can be at the forefront of this shift, capitalizing on the opportunity to build innovative activities for students built on the compelling content and real world science that oceanographers can bring to the table.

The trick will be, can we really practice what we… well… practice?

Blog Roundup #1 – Ocean Science and More

If you follow this blog and my twitter feed, you can probably guess that I have a lot of interest in the fields of data visualization, education, ocean science and web development, and especially how those worlds intersect. Each of these subjects is incredibly diverse, which makes it difficult to stay on top of new developments that are of personal interest.

In the past, one would have subscribed to several broad-ranging magazines in the hope that a few relevant articles might appear each year. But in the Internet age of blogging, micro-reporting, social networking, and web sites dedicated to every niche imaginable, the resources for personal knowledge development are immense. This is both a blessing and a curse.

To help weed through the chaff, I hope to occasionally share some of my favorite web sites and blogs – provided in easily digestible chunks for the busy educator or scientist.

This first roundup includes five of my favorite ocean and climate science related sites. Here they are in no particular order.

1) Community Collaborative Rain, Hail & Snow Network Blog – CoCoRaHS is a nation-wide network of volunteer observers who measure precipitation around the country. The maps and data on their main site is awesome, but the community blog features short synopses of major precipitation events. Each post includes lots of neat maps, and is written in easily understandable language.

2) GLOBE Scientists’ Blog – The GLOBE project enables classrooms around the world to collect environmental data that is used by scientists in their research. Their Scientists’ blog highlights the cool science that students can be involved in, and often features suggested activities.

3) Marinexplore Blog – Marinexplore is a relatively new company that is trying to build a comprehensive data portal that allows users to peruse and download a large variety of ocean datasets. Their blog is primarily devoted to promoting feature updates, but occasionally it includes some neat data visualizations and stories showcasing the datasets available on the site and the kinds of research that can be accomplished with them.

4) RealClimate – RealClimate is perhaps one of the top environmental blogs on the internet (at least when considering blogs written by scientists), and is certainly one that scientists, the media and educators regularly follow for analysis on recent developments in climate science. While the site is dedicated to making climate science more accessible, many posts are arguably rather high-level. However, it’s a great place to go when you want to look beyond the headline and learn more about how data on a global scale is processed, interpolated and modeled to better understand climate processes.

5) NOAA News – The U.S. National Oceanic and Atmospheric Administration is tasked with monitoring and forecasting weather and climate around the globe (not to mention their impacts on fisheries and humans). As a result, following their news feed is a great way to stay informed on all the cool things that NOAA does. Whether it’s the launch of a new weather satellite, a recent report on the health of fish stocks, a new system for issuing storm warnings or a recent national climate analysis, there are plenty of cool things to learn about, courtesy of your local U.S. taxpayer.

Streamflow and Conductance on the Delaware

Conductance vs. Streamflow on the Delaware River at Trenton, NJ

Rivers play an important role in our ecosystem. They provide water for drinking and irrigation of crops, a habitat for fish and other organisms, and routes to easily transport goods. For these reasons and more, it is important to monitor the quality of river water, including its physical, chemical, and biological characteristics.

One often measured parameter is specific conductance. Conductance is a measurement of a substance’s ability to conduct electricity and is related to the amount of ions, like salt, that are dissolved in the water.

Where rivers meet the ocean, the salt typically comes from seawater flowing upstream into the river. How far upriver the saltwater can reach (often called the salt front or salt line) depends greatly on an estuary’s type and the current streamflow.

Further upstream, where the ocean doesn’t have as much influence, the amount of dissolved salts in river water is generally related to how much precipitation there has been. When rainfall is light, more water on land can evaporate before it reaches the river, which concentrates the amount of dissolved salts in the water that remains. When rainfall is heavy, water tends to flow more quickly into rivers and streams, with smaller concentrations of dissolved salts.

The image above shows the relationship between river flow (discharge) and conductance over a 3+ year period on the Delaware River in Trenton, NJ. In general, the conductance is quite low, and well below accepted salt front cutoffs of ~400-1,000 micro-Siemens per centimeter, which correspond to chloride concentrations of 100-250 milligrams/liter. However, there is clearly an inverse relationship between conductance and discharge. When discharge is strong, water conductance is low, though it never gets below ~100 µS/cm. Likewise, when discharge is light, conductance is 2-3 times higher. While the salt concentration on the Delaware River near Trenton is generally low, it does depend on the streamflow.

Knowing the location of the salt front is important, especially on rivers where water is drawn for human consumption or irrigation, and for protecting riverine infrastructure like ships that corrode more easily in salty water. The Delaware River Basin Commission regularly monitors the salt front location in order to control its location by storing and releasing water in reservoirs upstream.

RTD Activity Idea: Monitoring Streamflow

Streamflow over the course of 2012 from the USGS streamgage in Trenton, NJ

The task of monitoring the nation’s numerous streams and rivers falls to the United States Geological Survey. The USGS maintains a large network of instruments that record streamflow, water height, temperature, conductivity, water quality and several additional environmental variables. One of the chief uses of this network is to monitor the occurrence of floods and droughts.

Thanks to USGS’s National Water Information System, this data is easily accessible for students to access and visualize, allowing them to investigate river conditions at nearby locations or from across the nation.

Real-time Data Project

Here is a quick activity students can use to investigate current streamflow conditions and compare them with historical norms.

  1. Go to the Current Streamflow Map on the USGS WaterWatch site and select a state.
  2. Click on a station and note whether it is currently above, at, or below normal conditions, as denoted by the color of the dot.
  3. Click on the station ID number. This will take to you the station’s summary page.
  4. In the pull-down list, select “Time-series: Daily data
  5. The top of the page includes some basic information on the station, including its location, a photo of the station, and (for some stations) the upstream drainage area. Underneath this information is a box to customize the graphs appear on the page.
  6. Select “Graph w/ stats” as the output format and enter a date range you’d like to visualize. (Here’s an example that displays data from Trenton, NJ for all of 2012.)
  7. Find the graph for discharge or gage height and compare how the measurements (shown in blue) compare with the historical average (shown in yellow).
  8. If you choose a full year (i.e. from January 1st to December 31st) you can quickly get a good idea of the annual differences and seasonal cycle at a station. (For example, for the Trenton station above, the highest average streamflows are typically seen in March and April, while the lowest occur in the summer and early fall.)
  9. Now that you have the hang of it, you can create graphs for individual years to compare them with each other, or you can look up data around specific events you know of, like major rain storms or droughts.

Engaging Questions

Here are a few questions students can think about before they start their research.

  • What do you know about floods and droughts? What causes them? What impacts do they have on the environment, ecosystems and people?
  • How do you think scientists study river flow? (The two primary methods are gage height and streamflow.)

Suggested Research Questions

Here are several questions students can try to answer by looking at the data.

  1. For your selected station, how does the most recent measurement compare with the current streamflow status (i.e. percentile class) shown on the map?
  2. How long has the station be at that state?
  3. What times of year have the highest streamflow? Which times have the lowest?
  4. Were there any times during the year where the streamflow was exceptionally high or low? Do you have any idea what may have caused these observations?

Relevant References

The WaterWatch web site, also maintained by the USGS, aggregates data from the entire stream gage network into a great set of maps, highlighting the current streamflow, drought and flood conditions around the country. If students are interested in looking at current or past conditions across the nation as a whole, this is a great place to start.

Streamflow on the Delaware

A 1-year graph of river flow on the Delaware River at Trenton NJ

Scientists who study river streamflow do not have an easy job. Unlike many weather measurements like temperature, pressure or humidity that change with more predictable variation throughout the course of a year, streamflow is more closely correlated with major rain and snow events. These events occur sporadically throughout the year, often in large doses.

The graph above is a good example of this complexity. The data shown was measured from a stream gauge on the Delaware River in Trenton, New Jersey. The daily mean streamflow (also referred to as “discharge”) from the most recent year is plotted in red, ending April 11, 2013. The long-term average streamflow statistics are calculated from a 99-year data set collected between 1913 and 2011.

The mean daily streamflow includes many large peaks over the course of the year. These peaks correspond to major precipitation events that occurred in the upper Delaware river basin. On the other hand, the lines showing the long-term average streamflow change more gradually throughout the year, with the highest streamflows observed in the spring (especially this week), and lower streamflows in the summer and fall.

Looking at this data, several interesting observations can be made.

  • In October 2012, Hurricane Sandy hit New Jersey causing extensive damage, however the observed streamflow during this time was not as high as some of the other events. As it turned out, most of the damage was caused by coastal flooding and high winds and not from flooding rivers.
  • Over the course of the winter, several large events were observed. These correspond to the major nor’easter’s that passed through the area, including the (strangely-named) winter storms Nemo and Saturn.
  • Last month was unseasonably cold and, while there was a nor’easter early in March, the month also ended up unseasonably dry. However, following today’s rainstorm, it is likely that the streamflow will rise to the more typical values expected during this time of year.

Ultimately, when studying rivers it’s important to remember that individual events will not always neatly line up with long-term averages, but over time, the trends should match.

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