This is the third installment from Dr. Czajkowski Last night, we had snow here in Colorado. In my front yard in Boulder, we had about 23 centimeters of snow. Three kilometers to the east, at Foothills Lab (close to the GLOBE offices), the “official” reading ws 17 centimeters — a six-centimeter difference of 3 kilometers. This difference is real — snowfall amounts are often greater closer to the mountains.

Hi All,

Things are continuing to go well with the surface temperature field campaign. As of December 8, 2008, there were 317 surface temperature observations from 31 schools were added to the GLOBE website.

Major Winter Storm in the United States

There is a major winter storm in the center of the United States this Tuesday, 9 December, 2008. This map is for 1:00 p.m. Eastern Standard Time which is 1800 UTC. This low pressure system with its associated warm front and cold front is producing a lot of rain, “wintry mix” (rain and snow, pink shades in figure 1), and some snow in the Midwest. You can also see that there is a cold high pressure system in Nevada and Idaho.

Figure1: Surface weather map 9 December 2008, The radar shows snow in the blue shades and the heaviest rain is shown in black. Figure from http://www.rap.ucar.edu/

There have been some pretty extensive snowfall in the United States this fall and early winter. But, you can see from the figures below that there was actually more extensive snowfall cover in 2007. By the weekend the weather pattern in the United States is going to change to have a storm in the western United States and warm weather in the eastern United States. This storm should give significant snow out west and to the Rocky Mountains. This will make the weather in the Great Lakes warmer.

Figure 2: Snow cover and depth from NOAA for 9 December, 2008 .

Figure 3: Snow Cover in the United States for 8 December 2007 from NOAA.

Here are schools that have entered data so far in the field campaign:

More and more schools are participating and getting their data on the GLOBE website. Keep up the good work.

Roswell Kent Middle School, Akron, OH, US [9 rows]
Dalton High School, Dalton, OH, US [8 rows]
Chartiers-Houston Jr./Sr. High School, Houston, PA, US [2 rows]
Lakewood Middle School, Hebron, OH, US
The Morton Arboretum Youth Education Dept., Lisle, IL, US
Peebles High School, Peebles, OH, US [25 rows]
Gimnazjum No 7 Jana III Sobieskiego, Rzeszow, PL [6 rows]
Penta Career Center, Perrysburg, OH, US [3 rows]
Canaan Middle School, Plain City, OH, US [2 rows]
Mill Creek Middle School, Comstock Park, MI, US [8 rows]
Brazil High, Brazil Village, TT [9 rows]
Kilingi-Nomme Gymnasium, Parnumaa, EE [10 rows]
Swift Creek Middle School, Tallahassee, FL, US [3 rows]
National Presbyterian School, Washington, DC, US
Maumee High School, Maumee, OH, US [5 rows]
Whittier Elementary School, Toledo, OH, US [2 rows]
Huntington High School, Huntington, WV, US [8 rows]
Warrensville Heights High School, Warrensville Heights, OH, US
Bellefontaine High School, Bellefontaine, OH, US [6 rows]
Oak Glen High School, New Cumberland, WV, US [12 rows]
Nordonia Middle School, Northfield, OH, US [4 rows]
Orrville High School, Orrville, OH, US
Bowling Green Christian Academy, Bowling Green, OH, US [6 rows]
McTigue Middle School, Toledo, OH, US [3 rows]
Highlands Elementary School, Naperville, IL, US [2 rows]
South Suburban Montessori School, Brecksville, OH, US [3 rows]
John Marshall High School, Glendale, WV, US [30 rows]
Birchwood School, Cleveland, OH, US [9 rows]
Hudsonville High School, Hudsonville, MI, US [7 rows]
The University of Toledo, Toledo, OH, US [4 rows]
Main Street School, Norwalk, OH, US [16 rows]

Stay Dry.
Dr. C

A series of guest blog entries by Dr. Kevin Czakjowski on the 2008 Surface Temperature Field Campaign will be interleaved with the regular Chief Scientist blogs. See the Introduction to the Surface Temperature Field Campaign.

I’ve often written about clouds on this blog. They are so easy to observe. Today I’m writing about birds since they are easy to observe as well.

It’s fun to watch birds. Many people spend their lives counting how many birds they have seen over their lifetime. I started doing this recently as well. But I find the more interesting part of my “life list” tends to be notes about what the birds are doing. For example, “We saw a half-dozen Yellow-Headed Blackbirds foraging on a lawn in the middle of a blizzard,” or “The fledgling Kestrels were learning how to fly under the watchful eye of both parents,” or, “At sunrise, we watched the Crows fly from the foothills to the west into town for a day of feeding.”

Although a pair of binoculars helps in watching those birds that are small or far away, you can see an amazing amount close up. This is particularly so for tamer ducks or geese. In the United States, we often see Mallards or Canada Geese (Figure 1). And many are not too afraid of people, so you can watch them without disturbing them too much.

Figure 1. Male Mallards (right) swimming with a Canada Goose. Little Dixie Lake, Boone County, Missouri, U.S.A.

Mallards have an interesting way of feeding. Their front ends go under water and their back ends tip into the air. This is called “dabbling” (Figure 2). Mallards eat mostly plants – grains, seeds of some trees, bulrushes; but they also eat some animal matter as well, such as mollusks, insects, tadpoles, snails, and so on.

Figure 2. Dabbling Mallards. Also at Little Dixie Lake

Unlike watching clouds, you can “watch birds” without looking at them. When I was a teenager, I went birding with a blind man on the island of Oahu in Hawaii. He could tell what birds were around simply by their calls – and maybe a little bit from the noise the birds make as they move around, since some species sit in one place, and others flit around. He would describe to me what the bird looked like and point in the direction the sound came from. I met another birder who often observed birds from their sound. He starting doing this because he was a runner, and he didn’t want to have to stop and look. And knowing the bird sounds is useful when you simply can’t locate a bird hiding in a tree or bush. And you don’t need binoculars.

It’s important to stay far away from wild birds or their nests. During nesting seasons, many parks and nature reserves close nesting areas so that the birds can raise their young undisturbed. Also, you shouldn’t feed the birds in wild places. If you want to watch wild birds, you should keep your distance and use binoculars. Or watch them from a blind, or if you are lucky enough, through the window of your home or school.

Birds and the Seasons

The migration of birds in the spring and fall has thrilled people for centuries. In North America, we like to hear the honking of geese flying overhead during the spring and fall. The Canada Geese fly in large V-formations. This enables the geese to the rear to benefit from the air currents created by the geese in front. If you watch closely, you will see them change places once in a while.

Although you can enjoy birds any time of year, the best times to watch birds is in the spring, when the males are singing to attract mates. Each species has a different song, and the songs can vary from place to place. Or even, though less so, from bird to bird. At this time, it’s even more important to keep your distance and use binoculars to watch them.

Why do birds migrate? No one knows for sure, but it probably has to do with finding food and a safe place to make a nest. And this will vary, like migrations, with the type of bird. In the far north, for example, there are fewer predators that could survive through the harsh winters, so nesting there might be a bit safer for birds that nest on the ground during the summers. Insect-eating birds won’t want to spend much time in an area when the temperature is too cold for insects.

One interesting topic that scientists are studying now is how climate change affects bird populations. Many scientists have found that birds arrive earlier in the spring than they used to. Also, some birds are extending their ranges northward. In the GLOBE Seasons and Biomes/IPY Pole-to-Pole video conference (see March 2007 blog), one of the teachers noted that Magpies were reaching farther northward into Alaska, for example. Scientists continue to try to sort out the role of climate change in the changes of numbers of different types of birds. There are many other factors to consider, such as the number and type of predators, changes in land use, and the use of pesticides.

What birds are you seeing this season? Ask older members of your family if the types of birds are different now, or if their numbers have changed.

And, if you are interested in further information about observing hummingbirds, go to This Week at Hilton Pond.

I asked a climate scientist at NCAR, Caspar Ammann, to review the previous blog, and he brought up some interesting points that I thought I would talk about a little bit further. I am hoping this will inspire some of you to play with the data a little bit, in order to get a better “feel” for what makes the trends at the GLOBE sites “uncertain.”

The effect of extreme values on the trend line

Let’s start with the Jicin, Czech Republic, annual average temperatures. But this time, we will include 1996:

Figure 1. For GLOBE data at 4. Zakladni Skola in Jicin, the Czech Republic, change of trend from leaving out the first point.

In the figure the red points are those used for Fig. 2 of the previous blog. You see the trend, 0.04 degrees Celsius per year. If we add the point from 1996, the trend more than doubles – to 0.1 degrees Celsius per year – 1 degree Celsius per decade.

But 1996 might be a cold year. Remember – weather and climate vary from days to weeks to years to decades.

2001 was a cold year, too, relative to the surrounding points. What if we left 2001 out? How much would you expect 2001 to affect the trend? Note in Figure 2 that there is almost no effect. This is because 2001 is close to the middle of the data record. This makes sense: if you drew a straight line through the points by eye, you would be influenced more by the points at the beginning and end of the time series.

Figure 2. For same dataset, but ignoring the cold point in 2001.

Now, you might think that you should get rid of both years. Maybe they are not representative of the long term trend. Something happened in the Jicin area to make it a really cold year in 1996, and a really warm year in 2001. So, you plot the data without either of the two points.

Figure 3. Same data as for Figures 1 and 2, but minus the averages for 1996 and 2001.

Now we are back to the trend in the first graph – 0.04 degrees Celsius per year!

Someone might look at Figure 3, and say that the average temperatures are just going up and down with time, like the seasons. And, that the trend is just because you didn’t have two (or three, or four) complete oscillations! You couldn’t really say this person isn’t right without having temperature measurements from before 1996.

Obviously, the actual value of the temperature trend depends on how you look at the data! You might try this exercise for other stations in the data provided in the last blog.

Let’s try this exercise for the global points in Figure 7 of the last blog:

Table: Global Annual Average Temperature minus the 1961-1990 Mean. Source, Climate Research Unit, Hadley Centre, UK.

(The alert reader will notice that Figure 7 in the previous blog is slightly different now – I had accidentally included data for 2008, which is incomplete.)

Figure 4. For the most recent 12 years of the Hadley Climate Research Unit data, the effect of ignoring “extreme” points in the time series.

Note from Figure 4 that the slope varies depending on the data selected, but that the trends remain positive.

Reducing the influence of extreme points by smoothing

Recall last time that I took out the seasons because I thought they might affect the trend. Climate scientists average in time to get rid of the effect of large year-to-year changes like the ones in 1996 and 2001.

To show the effect of smoothing the data for Jicin, I will do a “three-point running mean average.” This means that I will average the first three temperatures and the first three years. That is, I will average

7.7500
8.8500
9.2300 to get 8.61

And I will average the years, too

1996
1997
1998 to get 1997

Then I will average the next three temperatures for 1997, 1998, and 1999 to get the temperature for 1998, and so on. Let’s say how this smoothing affects the data

Figure 5. For Jicin data, change in trend from smoothing the data.

And you might want to try four-point averages or five-point averages. The fact that the trend is positive, no matter what we do, gives us a little more confidence that there is a warming trend. Just as adding more stations would. But no matter how good the data in Figure 4, this is a trend only for one place – and only for 12 years.

Defining the average temperature

Unlike trends, which are affected by where the numbers are in time, the year doesn’t matter when you take an average. The larger the number of points, the less difference an odd year makes. Let’s do the averages for Jicin, starting with 2 years, then three years, then four years, and so on, for the complete record, to see how each new year affects the average temperature. The results are in Figure 6

Figure 6. For the Jicin data set, the average as a function of the number of points. To take the average, we start by averaging 1996 and 1997 (two points), then 1996, 1997, and 1998 (3 points), and so on.

As you can see, even the large changes at the end don’t really show up much in the average. And I think you can also see that, the more points in the average, the less one difference one more point will make.

Climatologists have chosen to take their average over 30 years. Thus the HAD.CRUT3 curve in Figure 7 of the last blog is relative to a thirty-year average – from 1961 to 1990.

Recently announced at the GLOBE Learning Expedition was the upcoming worldwide GLOBE Student Research Campaign on Climate Change, 2011-2013. This campaign will enhance climate change literacy, understanding and involvement in research for more than a million students around the globe. The GLOBE Program Office is encouraging students to contact the GPO with research ideas in areas such as water, oceans, energy, biomes, human health, food and climate. Please send your Climate Change Campaign research ideas to ClimateChangeCampaign@globe.gov.

With the upcoming GLOBE Student Research Campaign on Climate Change in mind, I thought it might be interesting to check for temperature trends in the data from GLOBE schools. (A preliminary version of the yearly-averaged GLOBE student data is included at the end of this blog.)

GLOBE was founded in 1995. By 1996, some schools were already recording temperature data regularly. This provides us with up to 12 years of data from some schools.

Figure 1 shows an example of a long record of monthly mean temperature.

Figure 1. Monthly average temperatures from 4. Zakladni Skola in Jicin, the Czech Republic. The straight line through the data in a “best fit” linear trend determined by least-squares regression.

Figure 1 shows strong seasonal changes, with monthly average temperatures ranging from below freezing to around 20 degrees Celsius. While there is a long-term trend, the large departures from the trend line indicate that the estimate of warming rate is rather uncertain.

I decided to re-compute the trends by taking yearly averages. If a month was missing, I assigned a mean temperature equal to the average of the data from the two surrounding months (Fortunately, such gaps occurred in the spring or autumn, when filling in the data like this makes some sense). If too many months were missing, I didn’t include the year in the averages. Figure 2 shows the yearly-averaged data for 4. Zakladni Skola.

Note that the “best-fit” line in Figure 2 still shows a warming - but a different value. This is the result of the uncertainty in the linear trend, from a purely statistical point of view. This is not surprising - even the yearly averages don’t fit on a straight line. In fact the warmest year is 2000, near the beginning of the record.

Figure 2. Average annual temperatures for the data in Figure 1. Note that the “best-fit” line still shows a warming, but a larger value.

We can reduce the uncertainty by adding more data. So I include data from five other schools in Europe in Figure 3.

Figure 3. Temperature trends for six schools in Europe, selected so that no two schools are in the same country. Represented are Belgium, Estonia, Finland, Germany, and Hungary, as well as the Czech Republic.

In Figure 3, the best-fit trend lines for all six schools show warming. Note that the most rapid warming rates are at the farthest-north latitudes. Figure 3 gives us some confidence that Europe has been warming for the last decade, but there are year-to-year changes that are much larger than the 10-year trend. These short-term changes tell us there is a lot of uncertainty in the trend lines, but the fact that there are six lines instead of one gives us a little more confidence that the result might be “real” for the roughly 10 years data were collected.

For comparison, we take three sites in the United States, selected for having a continuous data record (Figure 4). In this case, two out of the three sites actually show cooling! This is quite different from Europe. However, as in the case of Europe, the year-to-year changes are greater than the long-term trend.

Figure 4. As for Figure 2, but for three schools in the United States.

Such differences could be real. The maps of temperature changes in Figure 5 show that the trends over 30 and 100 years show a lot of variation. For both time periods, the figure shows that Europe is getting warmer. Both periods also show more warming at higher northern latitudes. Results for the United States are mixed. Between 1905 and 2005, temperatures were warming over the northwest United States but cooling over the southeast United States. However, temperatures were warming over most of the United States between 1979 and 2005, with the possible exception of part of Maine (northeast corner of the United States).

Figure 5. Linear trend of annual temperature for 1905-2005 (top) and 1979-2005 (bottom). Areas in gray don’t have enough data to get a good trend. The data were produced by the National Climate Data Center (NCDC) from Smith and Reynolds (2005, J. Climate, 2021-2036). This figure and an excellent commentary on recent climate change are found at www.ncdc.noaa.gov/oa/climate/globalwarming.html.

In this blog, I have avoided using statistics to estimate the uncertainty in the trends, but I think you can see two things. First, even with all this carefully-collected data, there is uncertainty in the local trends; but the uncertainty can be reduced by including more data in the same region. And second, the trends can be quite different in different parts of the world.

To close, I include two more plots. The first is a version of the well-known curve that shows Earth’s average temperature warming with time. I plotted the curve from data from the Climate Research Unit (CRU) of the Hadley Centre in the United Kingdom

Figure 6. Annual average temperature, averaged over the globe. From the UK Hadley Centre (www.cru.uea.ac.uk/cru/data/temperature/hadcrut3gl.txt).

Figure 7. Data from Figure 6, with linear trend based on data from 1996-2007, on the same scale as for Figure 2 and 3.

The second plot is based on data since 1996 and plotted on the same scale as for the GLOBE schools. Notice how tiny the change is! This is, of course, because some parts of the Earth were cooling or warming less rapidly. But there is much more information included in that curve - and hence a lot more statistical certainty. Also, the scientists who worked on the data worked very hard to remove the effects of changing thermometers or station location, beginning and ending of observations, and many other things that can cause artificial trends. (By the way, a plot of the averages of the nine GLOBE sites produces a very slight warming with time of 0.0018 degrees Celsius per year - with the temperature peak in the year 2000 really standing out).

Clearly, this simple-looking curve took a lot of careful work to produce!

GLOBE STUDENT DATA

Below are the data used for Figures 1-4. For details in processing see the text.

xxxx - missing data (see below)

Documentation of the data

Summary of Sites

GLOBE school locations

1. Hartland, Maine, USA
2. Utajarvi, Finland
3. Tahlequah, Oklahoma, USA
4. Karcaq, Hungary
5. Eupen, Belgium
6. Waynesboro, Pennsylvania, USA
7. Hamburg, Germany
8. Jicin, Czech Republic
9. Tartumaa, Estonia
10. Average of Temperatures 1-9

Yearly averaging

Missing months are “filled in” by averaging the surrounding months. This was done when one month was missing or two months was missing (very rare). Fortunately, the missing data tended to occur in the spring or autumn, when the missing temperatures would be expected to be between the temperatures of the neighboring months. The average was then computed by summing up the data for all 12 months and then dividing by 12.

Average of all nine sites

The average is found by summing up the temperatures in columns 1 through 9 and then dividing by 9. If a temperature is missing (as in the first row, 1996), an average is not computed. Why do you think we did it this way? Two out of the three sites (3 - Tahlequah and 6 - Waynesboro) are the two warmest of the nine, and the third (8 - Jicin) is in the middle of the temperature range. If we used the average of those three points, it would make the average temperature in 1996 too warm.

NOTE: The data here are reported to two decimal places, while some of the data used for the graphs has three or four decimal places, so results might vary slightly from the results shown here.

What can be done to “improve” the dataset? We will be calculating averages for other schools with long temperature records and adding them.

I’m going to interrupt blogging about surprising liquid puddles and soil temperature to talk about the Second Pole-to-Pole Videoconference, which took place yesterday (8 April 2008). Several scientists participated, as did five schools: in Ushuaia, Argentina, the Escuela Provincial No. 38 Julio Argentina Roca; and in Alaska, the Randy Smith Middle School (Fairbanks), Moosewood Farm Home School (Fairbanks), Wasilla High School (Wasilla), and Innoko River School (Shageluk). The Web Conference was hosted by the GLOBE Seasons and Biomes Earth System Science team, at the University of Alaska at Fairbanks.

Figure 1. Locations of the schools in Alaska. Courtesy Dr. Elena Sparrow

Flgure 2. Location of Ushuaia, which is near the southern tip of South America. Part of Antarctica appears on the southern part of the map.

The focus was on climate change, in particular:

1. The most important seasonal indicators (things that change with season)
2. Whether they are being impacted by climate change (if so, how?)
3. How students could study these indicators to see if they are impacted by climate change.

As was the case last year, the students had an opportunity to ask questions of the students at the other schools as well as the scientists, but the conversation was more structured. We organized the conversations into three rounds. In Round 1, the Alaskan and Argentinean students were to ask each other about signs of seasonal change or share their own observations. In Round 2, the focus was on how to narrow questions down enough so that students could investigate them. And in Round 3, we were supposed to discuss the ways the investigations could be done.

The questions in Round 1 were wide-ranging. Why do leaves change color? Why is the soil frozen when the air is warm? Does the melting of permafrost cause damage to buildings and trees? Are glaciers disappearing? Do scientists use Native knowledge in their research? How does climate change affect plants and animals?

We learned that soil below ground warms and cools with the seasons more slowly than the air, and – the farther you go down, the less the temperature changes (this is also discussed in the previous few blogs). We also learned that the changes in the lower layers of the soil took place after the changes higher up (in scientific terms, the changes in the lower layers lags the changes in the upper layers). So a student was able to guess that late summer is the best time to test for permafrost, rather than the height of summer, when the sun angle is the highest.

We discovered that scientists are using Native knowledge in their research in many parts of the world, including not only Alaska and Canada, but also in Australia. We learned that magpies are coming farther north to Shageluk, and there are more pine grosbeaks than there used to be, although a student in Fairbanks didn’t notice any changes. We also learned that tree line is moving up in the mountains near Ushuaia.

In Round 2, questions focused on some fascinating things to investigate, including changes in the snowboarding season (of interest to students in both hemispheres), changes in temperature and precipitation, and succession of species after wildland fires. In fact, the students at Shageluk are already investigating the succession of species of some land recovering from a forest fire (see pictures at the Shageluk web site). The discussion of temperatures taught us the difference between maritime (Ushuaia and Wasilla) and continental (Fairbanks and Shageluk) climates: Ushuaia rarely gets below freezing, but Fairbanks has temperatures as low as -40 (same in Fahrenheit and Celsius), although such cold temperatures aren’t as common and persistent as they used to be). The discussion of snowboarding led to suggestions of investigating how long ski areas remain open, interviewing someone at a ski area about what conditions are good for snowboarding, thinking about what makes snow last (amount of precipitation, timing of precipitation, temperature). Two intriguing observations were that there were both more cumulus clouds in Ushuaia than there used to be, and more heavy rains.

With so many ideas generated in Round 2, some investigations were already outlined in some detail by the time we got to Round 3 – especially related to snowboarding. But snowboarding ideas continued to come up. A ski area had closed in Ushuaia, because its elevation was too low in the warming climate; and students in both hemispheres thought snowboarding might be an interesting thing to investigate together. Since the seasons are opposite, the study could be continuous.

Some new ideas also emerged about items to investigate. How about looking at when people take off or put on snow tires? Is that a good indicator of climate change? What about using frost tubes to monitor freezing and thawing in the soil in Ushuaia as well as Alaska? And how would frost-tube measurements relate to air temperature or the times that lakes and rivers freeze? And one could investigate the long-term seasonal geographic changes in diseases (mosquito-borne diseases, corn diseases).

It was pointed out to us that using a simple variable like temperature could yield some fascinating results beyond averages and simple trends. Is there a trend in how many days that the temperature stays above freezing? How about for the number of days when temperatures stay below freezing? How does this relate to precipitation? Clouds?

Also, we were reminded that not all changes we see are due to climate change – we humans are changing our environments in many other ways, such as destroying wilderness areas. And that trends we see in a few years can be quite different from the long-term trend. (That is, one cold winter doesn’t mean that it is getting colder on the long term.)

Through this rich mix of ideas for research topics and data to look at, the students continuously asked about each others’ lives. One of the most fascinating exchanges took place toward the end of the videoconference, when a student from Alaska asked the students in Ushuaia what kind animals they had and what kind of wildlife they ate. The Ushuaia students listed foxes, llamas, beaver, rabbit, birds, and penguins as the animals they had; and said that they ate rabbits, fish, and some beavers (but mostly tourists ate beavers). The beavers were apparently introduced to the region in 1946, and there are no natural enemies, so people are being encouraged to eat them.

A student from Shugaluk closed the discussion section of the conference by putting things in perspective. Yes, skate boarding and dog mushing are interesting, but for the Native peoples of the far North, their very way of life is being threatened. Earlier, a student in Ushuaia said that a glacier that was supplying water to the city was melting and would be gone in a few decades, leading to a shortage of drinking water. As one of the scientists said earlier, like the canary in the coal mine that warned of dangerous gases in a mine– the people in the Polar regions are the first to see the real danger in climate change. We need to remember this as we begin to take steps to try to slow down climate change and its impacts.

NOTES IN CLOSING:

There will be a web chat and web forum April 10-11. The purpose is to help students develop research ideas and projects, and interact with scientists. Links to the chat and forum can be found on the Pole-to-Pole Videoconference page of GLOBE Web site.

Three PowerPoint presentations describe the science and people of Ushuaia. They are also available on the Videoconference page at the above link.

Finally, I recall promising a student from Fairbanks that we would return to the topic of leaves changing color. Since we didn’t follow up on this question, I thought I would include a discussion here. The leaves change color because the chlorophyll, which gives the leaves their green color, disappears in the fall, so that other chemicals in the leaves give them their color. The chlorophyll, of course, is involved in photosynthesis, which provides plants the energy to grow. Different types of trees change different colors. For example, some maple trees turn bright red, while aspen trees turn yellow in the autumn. The weather actually affects how bright the colors are in the fall. In long term, the climate also affects the trees that can stay healthy in a given place. Thus the mix of trees, and hence the colors could change over many decades.

More information is available about leaf color under the Seasons and Phenology Learning Activities, Activity P5 “Investigating Leaf Pigments” in the Earth as a System Chapter of the GLOBE Teachers’ Guide.

The seasons and Biomes project is an effort to engage students in Earth system science studies as a way of learning science. It is a timely project for this fourth International Polar Year with many and intense collaborative research efforts on the physical, biological, and social components and their interactions. Changes in the Polar Regions affect the rest of the world and vice versa, since we are all connected in the earth system. I encourage students to conduct their own inquiry whether collectively as a class or in small groups, or individually. Students can use the many already-established GLOBE measurements in the areas of atmosphere/weather. soils/land cover/biology, hydrology, and plant phenology in their local areas (You can access the protocols by clicking on “For Teachers” on the menu bar at the top of the GLOBE homepage.) Soon there will be new measurement protocols such as fresh-water ice freeze-up and break-up protocols and a frost-tube protocol that will be posted on the GLOBE web site. Students can conduct a study on things that interest them as part of the upcoming GLOBE Student Research campaign.