Science is – more than anything – about asking questions about Nature. And it’s a lot more fun to discover the answers from your own data, than to read about them in a book. It doesn’t matter that someone else found the answer earlier. It’s important for you to find out how to discover nature’s secrets on your own.

I already knew about the relationship between crickets and temperature. But it was tremendously satisfying to re-discover that for myself. (Do you remember the cricket blog?)

One message that I hope you have heard is that you can do some simple science investigations without many tools. You can do some simple investigations without buying expensive equipment. The cricket measurements can be made with a clock and a thermometer. You can take snow measurements with a ruler. Does the snow cover vary from one place to another? With time? You can test to see if the auditorium heats up when you fill it up for parents’ night or a special performance or speech. The instruments needn’t be expensive. Even an uncalibrated thermometer can tell you whether it gets warmer in the auditorium, for example.

Another message that I would like to leave with you is not to be afraid to ask questions. Your textbook might not be right. When I was just starting out as a researcher, my professor told me to take a textbook, open it up, and point to a random page. He said that something on the page was probably wrong in some way, and it was my job to find out. That’s the way science is. We keep learning. A fundamental part of that learning is carefully observing nature.

I feel extremely lucky to have seen the science related to greenhouse-gas warming of the Earth develop from a simple idea I first heard in the 1970s to an idea that is largely accepted by the scientific community today. I also feel lucky to have seen geologists accept continental drift. The process of scientific progress, as you may have seen from arguments in the media, is not always pleasant. It can even be painful. People have passionate opinions on both sides. I just received a long and somewhat desperate paper from a long-time friend and colleague who still doesn’t accept that human-generated greenhouse gases are responsible for the warming of the planet. But there is considerable evidence from observations and models that he is wrong.

Others who know less about science or who don’t want to accept the warming of the planet by us write things on the Web that can be easily exposed as false. Thus I have from time to time written about “misconceptions” about climate change. When you read about the changing climate – or any other aspect of nature – on the Web or in newspapers or magazines, remember your basic science. And remember to ask questions.

I have probably been less successful in writing about other countries. Writers are told to write about what they know – and I know the weather and climate of the United States the best, since I live here. I can observe the temperatures and puddles and snow and fires in Boulder, Colorado, because I live here. Perhaps in future blogs we can have guest bloggers from other countries to share observations and ideas.

What will be my future?

After I leave GLOBE, I will be a full-time scientist at the National Center for Atmospheric Research. I will be doing research on how to represent the warming and moistening of the atmosphere by the surface and its vegetation in computer models used to predict the weather and climate. The plot in Figure 1 shows something I am interested in: how daytime surface temperature (related to how much the air near the surface is heated) and green plant density. Figure 2 shows where the data were collected.

Figure 1. Plot of the Normalized Differential Vegetation Index (NDVI), which describes the amount of green plants in a given area, against surface temperature measured by a Heiman radiometer. On the Eastern Track, which is in southeast Kansas, areas with lots of green (in this case grass) tend to be cooler, something we know from walking barefoot. On the western track (in the Oklahoma Panhandle), the surface temperature depends more on how wet the ground is than on vegetation, which is sparse. (For more about surface temperature, see the GLOBE Teachers’ Guide) The data were collected from the University of Wyoming King Air, flying along tracks shown in Figure 2, on 29 May 2002 (Western Track), 30 May 2002 (Eastern Track) and 31 May 2002 (Central Track). IHOP = International H2O Project.

Figure 2. Map showing the locations of the flight tracks in Figure 1. The “Radar Track” in this Figure is the “Western Track” in Figure 1. The low NDVI in Figure 1 tells us there is little green vegetation along the radar (western) track. This is consistent with less rain there.

After a short break, I will continue to contribute (though less frequently) to a blog at another site here at the University Corporation for Atmospheric Research (UCAR, to be announced later). I hope you will continue reading the GLOBE blog, which will be undergoing some exciting changes. These will be announced in the next blog by Dr. Ed Geary, the GLOBE Director.

I will be retiring on 25 December 2009. But I will still be working – more for the joy of it rather than for pay. Younger people can use the salary more than I can. I am looking forward to serving as President of the American Meteorological Society, which has 14,000 members around the world, but mostly in the United States and Canada (I am currently President-Elect). I also will be continuing in my weather and climate research, but will also take more time for my other passions – paleontology (Figure 3), birding (Figure 4), and clouds (Figure 5), as well as my family and friends.

Figure 3. Segments of a Baculite. This fossil is a type of Ammonite that is straight rather than coiled. It is related to the modern Chambered Nautilus or Squid. From the Upper Cretaceous, Wyoming.

Figure 4. Wild Turkey, photographed on road from Roswell, NM, USA, to Bitter Lake National Wildlife Refuge.

Figure 5. Cumulus clouds over the foothills west of Boulder, Colorado.

Please remember the joy that comes with observing your world. But look carefully. And remember that nature is full of surprises.

Peace

My husband and I start each day with a 2-mile walk at dawn, during which we observe the animals (deer, foxes, birds), talk, or just walk quietly. I think of many of my blog ideas while on this walk (or on the occasional walks I take on the open space near the office).

After we eat breakfast, we carpool to work. Since we work in two different buildings, he lets me off about 200 meters from where I work and then he drives to his building, which has covered parking. While walking to my building, I take special note of the birds (the other day a hawk and crow flying together) or clouds, sometimes pausing to take a picture. This walk takes me right by the rain gauge that NCAR has as a part of the CoCoRaHS that I have written about before. Sometimes I see someone taking the rainfall measurement.

After arriving at the office, I plug in my laptop (if I took it home overnight) and turn it on. While waiting for it to boot, I turn on my desktop computer and read my email. I was excited to see some comments about a paper that five of us just finished on tropical storm clouds carrying energy from near the surface to 10-14 kilometers and higher. The sender showed me and the other authors a couple of figures that showed the effects of the model resolution (related to the size of motions that the model can deal with directly) on how far air can rise in a cloud model. (A cloud model is designed to predict what the clouds will do). The most exciting thing about this particular paper is that we worked on it almost completely over the Internet. We rarely met in person (though some met at conferences and at the University of Oklahoma). The only person involved that I talked to (over the phone) was the lead author – and that was only once!

Figure 1. At my desk. Here, I’m reviewing a cloud poster that will be presented at a meeting this weekend.

By the time I finished reading the comments on the paper, a colleague (Dr. Fei) came in to tell me about a meeting he had attended the previous day. He told me that the group liked some of the work we had been doing over the past two years on altering the formulas in a model used to represent surface exchanges of heat and moisture in a numerical weather prediction model used for weather forecasting and research. We were going to be asked to present the results to a meeting in April. We talked about what we needed to do for this presentation, and some of the other tasks we were working on together. We will be doing a lot of comparison of the model results to observations. Once we are satisfied that our new version of the model (with the adjusted formulas) is better than the old one, we will change the old one, so that everyone using the model can benefit from what we found out.

After that, it was time for some GLOBE work.

We are working on a way to more easily access scientists when we need them for special events, like Web chats, video conferences, or judging student papers. Another GLOBE staffer (Dr. Sheila) and I had worked on this for a couple of years, getting input from the GLOBE community at the US Globe Annual Meeting in San Antonio, and a meeting for GLOBE and its Science Principal Investigators in Durham, New Hampshire. This morning, I finished writing a document that will be discussed next week. I sent a copy to Dr. Sheila to review before we shared it with others.

I then did some work on the next blog (on birds), looking at the first review that came in, and altering the blog in response to the comments. Each blog has three or four reviewers from the GLOBE staff, and occasionally a scientist outside of GLOBE looks at it if the blog is on a subject that I’m not an expert on; and sometimes even if I am.

Checking email, I discovered I needed to write another letter of recommendation for a young post-doc (someone with a short-term position – usually 1-2 years – right after they get their doctorate) who is looking for a university faculty job. I gathered the needed information, sent the letter as an email, and printed it out for mailing using snail mail, as they requested. I discovered that I needed to write a second letter for the same person, so I did.

By this time, it was time for lunch, so I went downstairs to the NCAR Cafeteria for about a half an hour. We talked about birding on this particular day (maybe because I had questions related to my bird blog). I stopped on the way back to the office to put a piece in a jigsaw puzzle outside the Director’s office. For years, there has been a jigsaw puzzle there for people to work on at odd moments of the day (for me, while waiting for something to come out of the printer, coming back from lunch, or between tasks – just to get up from my desk).

Figure 2. Working on the jigsaw puzzle – this one is basically done.

By the time I got back to my computer, some figures had arrived over the Internet for a paper that we just finished. There are several authors on this paper, because it deals with data that several of us collected in a field campaign in 2002. Each of the authors is reviewing it; and in the meantime, we are refining the figures and fixing minor things we know that are wrong. Dr. Fei is one of the authors. I checked each of the figures, saved them, and inserted them into the manuscript. I compared the captions to the figures, but found that no adjustments were necessary.

Then more emails arrived related to the paper on tropical clouds. This time the lead author had averaged the temperature in the updrafts that had reached 10-14 kilometers in altitude. We exchanged a few messages about whether the averaging time should be shorter than what he was using.

Dr. Sheila had reviewed my document and made several suggestions, which I considered and responded to before emailing it to several GLOBE staffers for a meeting next week.

By this time, it was almost 2:00 p.m., and I needed to post another blog for Dr. C. He sent me an email telling me it was coming, and I sent an email to Karen in GLOBE to stand by for whatever changes she would need to make. The blog arrived at about 1:50 p.m. I checked it for edits, and posted it after altering one figure slightly in Photoshop. There were some concerns about the other figure, however, and I noted that when I let Karen know the blog was posted. I also let Dr. C. know – and checked with him to make sure that he meant millimeters (rather than centimeters) in one part of the blog. He emailed back that he meant millimeters. I discovered the problem with the figure, cropped it, and sent the resulting image to Karen to put in the blog.

After all of this, I headed to a 2:00 p.m. meeting 20 minutes late, and discovered that everyone was coming back. Given this new-found freedom, I put another piece of the puzzle, and organized things for my trip home. When my husband arrived just after 3:00 p.m., several of us talked about the meeting and how NCAR could be saving money.

At 3:15, I went home, and then set up my computer to write a letter of recommendation for a student who is getting his Ph. D. in 2009. I finished at 5:00 p.m.

What have you noticed about this day?

Did you notice how much time I spent writing? And I wasn’t really working on the paper very much. This is not unusual – scientists spend a lot of time writing.

Also – did you notice how much time I spent on the Internet? I am currently working on two papers, and finished one last week. In all cases, the authors are scattered across the country. We hope that more GLOBE students will work together in this way.

Finally, I use math frequently – even simple stuff like averaging. Analyzing weather observations involves math. The models involve a lot of math, including a formula we were working on changing. Finally, analyzing the model output involves math.

Of course physics (and for me a little biology and chemistry) is important as well. The math and writing and Internet are all tools that help with science.

Some days are of course, different. For example, to collect data in field campaigns, we have to go where the weather is. Over my career, I’ve lived in several places – Dakar, Senegal; Taipei, Taiwan; Honiara, Solomon Islands; Guadalajara, Mexico; Mayaguez, Puerto Rico; and several places in the continental United States, while collecting data. Typically, we fly aircraft through the weather we are studying, along tracks we figured out far in advance – so that we can gather the data we need; gather data using radars (including Doppler radars), and use surface towers to make measurements near the earth’s surface.

This blog was inspired by a question at a recent video conference I had with teachers in Iowa.

Postscript: The paper was just accepted for publication.

Then again, this might not be too surprising.

Think of a typical science project, which starts with a hypothesis and some background, then goes on to describe methods, and then discussion and conclusions. That sounds to me a lot like “inference based on data.” Does it to you?

Do you know what is missing?

There is a very important next step: the testing of those conclusions by other scientists.

In practice, the first step is a “friendly review” of a scientific paper by a colleague. Many organizations require that scientific papers go through an “internal review” before the scientist submits it to a scientific journal. “Internal” means the reviewer or reviewers work for the same organization. The author of the paper needs to respond to the comments of the internal reviewers before sending the paper off to the journal.

The second step is anonymous peer review. The Editor of the journal sends the paper to two or three scientists who are experts on the subject of the paper. These “peer reviewers” are asked to go through the paper carefully, and comment on whether the conclusions of the paper are supported, and whether the paper prevents new results. The author has to correct any problems, and the reviewers get to comment on the corrections. Based on the reviewers’ comments, the editor will “accept” the paper so that it is published, “reject” the paper, or ask the scientist for further revisions.

Often, even before the paper is written, the scientist will present results at a scientific meeting. This is a good test of whether the work is robust or not. Often, questions at scientific meetings are quite helpful, and the scientist’s project is improved as a result. Discussions in the hall or during meals can be as useful as those at the formal sessions.

Figure 1. December, 2008 meeting at the American Geophysical Union. Photo by Kevin Czajkowski. Some scientists are presenting posters describing their results. Other people are just talking. In either case, the scientists are learning from one another.

Once other scientists become aware of the work, they can begin to evaluate the results through their own work. The other scientists find out either through seeing the first scientist speak at a meeting, from reading about the work in the journal article, or from word of mouth. This results in new papers, which may refine the first scientist’s conclusions, or perhaps show that the first scientist’s conclusions are wrong. These papers, too, go through the review process.

So – science is “self-correcting.”

Even so, science is full of “blind alleys” along which sets of observations seemed to make sense, and even predict the results of future experiments. But then, something isn’t quite right – and scientists realize an alternate explanation for all those observations and experiments.

Some famous examples of “errors” from history are:

• The planets having orbits that are perfect circles
• Space being filled with something called “ether”
• “phlogiston,” an element that was released when material was burned.

In these cases, the “correction” process took awhile, and you learn about it in your chemistry or physics classes. If you are not familiar with these concepts, you might want to do some research on the Web.

Here, I provide two examples of “self-correction” that happened quite rapidly. Both examples have to do with data from a large field campaign called GATE that occurred in 1974. During this field program, which involved 72 countries, scientists spent four months in Dakar, Senegal or in ships moored in the tropical Atlantic, taking measurements of the atmosphere and ocean with ships, aircraft, buoys, and a satellite (the first time satellite information was used in a large field program).

The first example involves measurements from aircraft of updrafts and downdrafts in thunderstorm clouds over the tropical ocean (or more accurately, cumulonimbus clouds, since there wasn’t much lightning). The aircraft would penetrate a single cloud, or cumulonimbus clouds arranged in a rainband or squall line. The scientists expected strong updrafts and downdrafts, but the updrafts and downdrafts sampled during GATE were surprisingly weak. The size and speed of these updrafts and downdrafts were reported in the literature, and followed by several papers on updraft and downdraft motions in cumulonimbus clouds in other locations over the tropical oceans.

A scientist wrote such a paper using aircraft measurements and submitted it to a scientific journal. The paper confirmed previous results. The paper went to the reviewers. At least one reviewer thought the paper was o.k. – After all, it was confirming previous results, basically strengthening the growing consensus that updrafts in cumulonimbus over the ocean were surprisingly weak – at least at altitudes below 5 kilometers, where the aircraft flew. But one reviewer somehow figured out that the author had been analyzing not the vertical speed of the air but the vertical speed of the aircraft! The authors had to withdraw the paper and do the data analysis over again.

The second example had to do with buoyancy of updrafts under fair-weather cumulus clouds, based on GATE aircraft data. GATE aircraft provided – for the first time, – abundant and usable measurements of temperatures and humidity just below cloud base, over the tropical Atlantic Ocean. One scientist was excited to find that the air feeding the clouds was buoyant, giving the clouds an extra kick. While updrafts beneath all clouds was warmer (buoyant) than the environment, the updrafts beneath the larger clouds was warmer and more buoyant than the updrafts beneath the small clouds. This made sense – the big clouds were growing more, so buoyant updrafts might be part of the reason the clouds were bigger, right?

Well, it turned out the reason that the updrafts were warmer was related to an instrument problem. Because the aircraft were flying over the ocean at altitudes as low as 30 meters above the surface, all the instruments, including the temperature sensors – were coated with salt from the ocean. (There are always some sea-salt particles in the air above the ocean.) When the relative humidity became high (which it does just below cloud base), the salt would absorb the water, which would liquefy, and this would release heat (condensing water releases latent heat). This warmed the temperature sensor, leading to artificially high temperatures. This effect was bigger for the bigger clouds because the sensors were exposed to humid updrafts for a longer time, so the air was warmer beneath the bigger clouds. Once the aircraft left the updraft, the air was drier, and the water on the sensor could evaporate again (and cool the sensor, making the air surrounding the cloud-base updrafts look cooler).

These results were presented at a scientific meeting – and the scientists at the meeting were quite excited. But the paper never got published, because of the discovery that the results had nothing to do with nature and everything to do with measurement error.

I was the scientist in the second example.

The inference based on the data looked correct to all of us, and thought to be reasonable by all of us. That is, until other scientists discovered the instrument problem, which happened after the meeting.

Looking back on this, this problem should have been obvious. There were measurements from three aircraft. On one aircraft, the technicians rinsed off the temperature sensor after every flight. On the second aircraft, the pilots deliberately flew through rain showers after each flight to rinse off the sensor – which didn’t happen if a rain shower wasn’t handy. And the temperature instrument on the third aircraft was rinsed only when the aircraft was required to go through rain (as would be the case when the aircraft were penetrating squall lines, for example).

And, you guessed it. The warming below clouds was greatest for the aircraft for which they did nothing, and the least for the aircraft with temperatures sensors rinsed daily!

So – when you do your science projects, and things seem to be working out right – remember that you might be missing something! But that is part of the fun of it.

I wanted to write a wrap-up for the surface temperature field campaign. Dr. LeMone posted a great discussion of the relationship between surface temperature and air temperature (scroll down to 6 January blog). I felt cold just reading about temperatures of –27 C.

Many of the observations from the field campaign have been posted but not all have yet. If you still need to get your data online, please do so soon, as students from around the world will be working on their inquiry-based research projects. They may want to use your data. Also, several schools were not able to participate in December so they took observations in January and some schools are still taking observations now.

Thus far, 58 schools have entered data for the field campaign and there have been a total of 1584 observations. If you add up all of the surface temperature, snow, clouds and contrail observations, there have been 36,432 observations taken during the field campaign. Could you image trying to take all of those observations by yourself? I couldn’t.

I am really impressed with some of the schools that had many observations submitted. The school with the most observations was John Marshall High School in Glendale, West Virginia, USA with 122. Other notable schools are: Peebles High School, Peebles, Ohio, USA (94), Dalton High School, Dalton, Ohio, USA (77), and Oak Glen High School, New Cumberland, West Virginia, USA (81), elementary schools Main Street School, Norwalk, Ohio, USA (90) and St. Joseph School, Sylvania, Ohio, USA (84). In addition, a couple of schools in Poland took a large number of observations, Gimnazium No 1, Sochaczew, Poland (72) and Gimnazjum No 7 Jana III Sobieskiego, Rzeszow, Poland (62).

This year the weather cooperated pretty well and many of you were able to observe the surface temperature with snow on the ground. The deepest snow depth (288 mm) was measured by students at Nordonia Middle School, Northfield, Ohio, USA. Fifteen of the lowest 20 surface temperatures recorded were observed by students from Moosewood Farm Home School, Fairbanks, Alaska, USA. The lowest surface temperature that they recorded was –32 degrees Celsius. Another cold surface temperature (-26 degrees Celsius) was noted by Gimnazium No 1, Sochaczew, Poland. All of the warmest surface temperatures were recorded by students at Brazil High, Brazil Village, in Trinidad and Tobago with temperatures of +35-50 degrees C.

Figure 1: Schools in GLOBE that participated in the surface temperature field campaign. Many are in Ohio because that is where I have funding for professional development.

Figures 2 and 3 show the relationship between surface temperature and snow in an area mainly covering Ohio, Michigan and West Virginia. These observations were not separated on the basis of water in the water.

Figure 2. Student observations of snow depth, 8 December, 2009.

Figure 3: Surface temperature as recorded by students on 8 December, 2008.

There is one thing to notice about the satellite imagery during this time period. Clouds obscured the ground most of the time. The image below, 7 December 2008, was the clearest image we could obtain of the Great Lakes regions. It seems that the observations in eastern Europe were cloud covered even more. The MODIS image depicts the surface temperature as the satellite went over and took observations on , 7 December 2008. The orange depicts part of Lake Huron that was ice covered.

Figure 4. MODIS Surface temperature product (MOD11), 7 December, 2008.

Here is the list of all of the schools that participated.
Roswell Kent Middle School, Akron, OH, US [37 rows]
OHDELA, AKRON, OH, US
Capital High School, Charleston, WV, US [6 rows]
Dalton High School, Dalton, OH, US [77 rows]
Chartiers-Houston Jr./Sr. High School, Houston, PA, US [28 rows]
Lakewood Middle School, Hebron, OH, US [10 rows]
Cloverleaf High School, Lodi, OH, US [60 rows]
The Morton Arboretum Youth Education Dept., Lisle, IL, US [9 rows]
Peebles High School, Peebles, OH, US [94 rows]
North Marion High School, Farmington, WV, US
Christensen Middle School, Livermore, CA, US [2 rows]
Gimnazjum No 7 Jana III Sobieskiego, Rzeszow, PL [62 rows]
Gateway Middle School, Maumee, OH, US [9 rows]
Penta Career Center, Perrysburg, OH, US [8 rows]
Canaan Middle School, Plain City, OH, US [28 rows]
Mill Creek Middle School, Comstock Park, MI, US [24 rows]
Brazil High, Brazil Village, TT [30 rows]
Kilingi-Nomme Gymnasium, Parnumaa, EE [42 rows]
Montague Elementary School, Montague, NJ, US [2 rows]
Swift Creek Middle School, Tallahassee, FL, US [19 rows]
National Presbyterian School, Washington, DC, US [15 rows]
The Bryan Center, Bryan, OH, US [16 rows]
Baltimore Polytechnic Institute, Baltimore, MD, US [2 rows]
Reams Home School, Wellington, OH, US [36 rows]
Maumee High School, Maumee, OH, US [16 rows]
Whittier Elementary School, Toledo, OH, US [6 rows]
Huntington High School, Huntington, WV, US [29 rows]
St. Joseph School, Sylvania, OH, US [84 rows]
Russia Local School, Russia, OH, US [24 rows]
Warrensville Heights High School, Warrensville Heights, OH, US [2 rows]
WayPoint Academy, Muskegon, MI, US
Gimnazium No 1, Sochaczew, PL [72 rows]
Moosewood Farm Home School, Fairbanks, AK, US [27 rows]
St. Michael Parish School, Wheeling, WV, US [14 rows]
Anthony Wayne High School, Whitehouse, OH, US [13 rows]
Bellefontaine High School, Bellefontaine, OH, US [36 rows]
Oak Glen High School, New Cumberland, WV, US [81 rows]
Barberton High School, Barberton, OH, US [37 rows]
Nordonia Middle School, Northfield, OH, US [34 rows]
Aurora Elementary School, Aurora, WV, US [13 rows]
Orrville High School, Orrville, OH, US [15 rows]
Bowling Green Christian Academy, Bowling Green, OH, US [26 rows]
Polly Fox Academy, Toledo, OH, US [18 rows]
McTigue Middle School, Toledo, OH, US [9 rows]
Highlands Elementary School, Naperville, IL, US [8 rows]
South Suburban Montessori School, Brecksville, OH, US [34 rows]
NASA IV&V Educator Resource Center, Fairmont, WV, US
John Marshall High School, Glendale, WV, US [122 rows]
Boys’ Village School, Wooster, OH, US [9 rows]
Birchwood School, Cleveland, OH, US [43 rows]
Lebanon High School, Lebanon, OH, US [9 rows]
Central Catholic High School, Toledo, OH, US [4 rows]
Eastwood Middle School, Pemberville, OH, US [18 rows]
Orange Elementary School, Waterloo, IA, US
Hudsonville High School, Hudsonville, MI, US [27 rows]
The University of Toledo, Toledo, OH, US [32 rows]
O. W. Holmes Elementary School, Detroit, MI, US [11 rows]
Main Street School, Norwalk, OH, US [90 rows]

That is all from this year’s surface temperature field campaign. Maps were prepared by Nancy Cochran and Timothy Ault of the University of Toledo.
Dr. C.

Thank you, Dr. C., and all the students and teachers who participated in this field campaign! – PL

It is true that volcanoes give off carbon dioxide. In fact, paleoclimatologists talk about “greenhouse worlds” with more carbon dioxide, much of which is thought to be from volcanoes. However, most of the time, the air at Mauna Loa is not influenced by volcanic gases released nearby. When air influenced by nearby volcanic gases is sampled, these data are not counted in the average. Similarly, at Cape Point, South Africa, which we visited during the GLOBE Learning Expedition, scientists try to avoid using data influenced by nearby Cape Town (see 11 Aug 2008 blog).

To see what the carbon dioxide trends are in different parts of the world, I went to the NOAA Earth System Research Laboratory Web Site). Here, you will find data from stations around the world. These measurements are taken at about 30 m above the surface. Figure 4 shows an example.

Figure 4. CO2 time series for Halley Station, Antarctica. From NOAA ESRL site (see text). The observations are the black points. The turquoise points are from the “Carbon-Tracker” model. USE graph without gap.

Just for fun, I looked at 15 such plots, and drew a line by eye (“faired” the line) to find the trend in carbon dioxide concentrations using the end points at the beginning (1 January 2000) and end (31 December 2008). Figure 5 shows what I did for the plot in Figure 4.

Figure 5. Figure 4 with the straight line I drew through the data (I tried to follow the black points, which are the observations). The values I read off are at the ends of the line, i.e., at the beginning of 2000 and the end of 2008.

Then I put the numbers in a table, and took the differences for each day. Figure 6 is a plot of the values at the beginning and end of the period for the 13 stations that didn’t have too much scatter. (The other two, in Europe, had considerable scatter, and higher rates of increase – around 2.6-2.7 parts per million (PPM) per year).

Figure 6. End points of the straight line drawn by eye through curves like that in Figure 3. Data from NOAA Earth System Research Laboratory/Global Monitoring Division.

It is interesting to see that the highest carbon-dioxide concentrations occur in the northern middle latitudes, where the most people (and cities, and factories, and cars) are. Even so, the carbon dioxide concentrations at the beginning and end of the period change little with latitude. Finally, the changes with time (over eight years) are about the same at all locations plotted. If we average the yearly trends, we find a carbon-dioxide increase of 2 PPM per year, with very little scatter (standard deviation 0.08 PPM per year, standard error 0.022 PPM per year).

Misconception: The warming pattern is related to the pattern of carbon dioxide concentration. Where carbon dioxide increases faster, the temperature is warming faster.

It is true the carbon dioxide has “weather.” Carbon dioxide concentrations near the surface can vary a lot (several tens of parts per million) from day to night, and from summer to winter at a given location (see 7 September 2007 blog) . Carbon dioxide concentrations tend to higher over more populated regions, as illustrated by Figure 7, with lower values over the ocean.

Figure 7. “Carbon-Tracker” model-based Carbon dioxide “weather” over North America based. The concentrations are the averages for a column of air. From http://www.esrl.noaa.gov/gmd/ccgg/carbontracker/co2weather.php.

However, as shown in Figure 6, the long-term trends in carbon dioxide don’t vary that much.

What then explains why some areas are warming more than others? Let’s start by thinking about what changes the temperature on a daily basis.

It is true that the “greenhouse” effect of both carbon dioxide and water vapor (which varies quite a bit) has an effect on temperature change through radiative processes. In fact, the water vapor content changes a lot more than the carbon dioxide content. Something closely related to “average column carbon dioxide content” is the “precipitable water,” or the amount of water vapor in a column, that, if condensed, would fall at the surface beneath that column. One can find examples of precipitable-water maps on the web. For example, visit http://weather.unisys.com/upper_air/ua_con_prec.html. You will find that precipitable water over the United States varies by a factor of five, ten, or more!

However, temperature changes near the surface are mostly driven by heating (or cooling) of the ground, and the ground in turn heating (or cooling) the air. Of course radiation plays an important part here, too. During the day, when the ground is heated, the heating is especially effective, since air warmed by the ground is buoyant. This buoyant air rises, carrying heat upward with it. Clouds also affect temperature change. Cloudy days are often cooler than days with clear skies, because less sunlight reaches the ground. Clouds at night “trap” heat near the ground, keeping the air from cooling off as much. The wind can bring in warmer air from the south and colder air from the north (in the Northern Hemisphere). And rain showers and thunderstorms also affect temperature.

(When you average over the whole Earth, many of these effects cancel – you are bringing heat to one area but taking it away from another. But, from the point of view of Earth versus space, only the radiative effects matter – those related to the mixture of gases in the atmosphere, and also aerosols and clouds. The other methods of heat transfer – conduction and convection, don’t work in the near-vacuum of space.)

The changes described above are rapid day-to-day changes – what we call weather. And the real question is why are some areas warming faster than others over decades? There are several reasons, depending on the part of the world we are thinking about. All of these are still areas of active research.

1. The warming of the high northern latitudes (Figure 1) is related to the reduction of time when the surface is covered by ice or snow. The warming of the high northern latitudes is often thought of as an example of a positive feedback loop: the more ice melts, the less sunlight is reflected away, which leads to more warming, which leads to more ice melting, and so on.

2. Uneven warming of the Earth causes a shift in the jet stream and storm track, which can influence temperature and rainfall. The best example of this is the highs and lows associated with continents and oceans in every introductory meteorology book. This influence of oceans versus continents is of course permanent except on geologic time scales.

But, in the last few decades, scientists have discovered that variations in the sea surface temperature over a few years influence where thunderstorms occur over the Pacific Ocean. The shift in the stormy areas influences the track of the jet stream, and hence weather downstream. Thus, for example, some locations in North America will have a greater chance of northerly winds aloft in some years, and thus have colder weather than when the northerly winds weren’t there.
Changes in the normal wind direction on the seacoasts influence whether or not there is upwelling, or water rising from lower levels. The water rising to the surface tends to be cooler, which cools the air temperatures over the adjacent land.

3. Scientists think that the loss of ozone over Antarctica has kept the temperatures at the South Pole from warming (See Figure 2). (may add two references here)

4. Changes in land use could be influencing the temperature trend in parts of the world. For example, an increase in green plants could lead to more sunlight being used for evapotranspiration and increasing the water vapor in the air at the expense of increasing the temperature. Another example is the warming produced in cities, not only be replacing vegetation with concrete (which heats up more readily when it’s dry), but also by the energy release associated with manufacturing, heating and cooling buildings, transport, and even human metabolism (see 7 Feb 2007 blog).

A post-script. The 16 January Science announces the impending launch of two new satellites, Japan’s GOSAT (Greenhouse Gases Observing Satellite) and US/NASA’s OCO (Orbiting carbon observatory). The GOSAT will be able to look at the relationship between carbon dioxide and weather patterns, while OCO will focus on carbon-dioxide patterns over longer times (a few weeks and longer).

Hardly a day goes by that we don’t hear about climate change in the media or from your friends. Not everything we hear is accurate. In this blog and the next one, I will describe some misconceptions about climate change that I have recently heard, and then describe what the situation really is.

Scientists are replacing the term “global warming” with the term “global climate change” because the climate isn’t really getting warmer anymore.

It is true that many scientists don’t like the term “global warming.” This is because it implies that the temperature is getting warmer everywhere, which isn’t true. I’ve often heard the analogy to a fever, as in “the planet has a fever.” Unfortunately, this analogy implies not only that the planet is getting warmer everywhere, but that it is getting warmer everywhere at the same rate. If you have a fever, the temperature is higher by about the same amount throughout the body. So, no matter where you measure the body temperature – either on the forehead, under the tongue, in the ear, or elsewhere.

In contrast to the fevered human body, the Earth’s surface temperature is warming at different rates at different places, and some places are even getting cooler. Figure 2 shows the annual temperature trend of the yearly averaged temperature from the National Climate Data Center (NCDC), taken from the 11 June 2008 blog. You can see that the greatest warming is in northern North America and Eurasia.

Figure 1. Linear trend of annual average temperature for 1905-2005. The gray areas don’t have enough data to get a good trend. The data were gathered by the National Climate Data Center (NCDC) from Smith and Reynolds (2005, J. Climate, 2021-2036). The figure and an excellent commentary on recent climate change are found at http://www.ncdc.noaa.gov/oa/climate/globalwarming.html.

Figure 2 shows the surface temperature change relative to the 1951-1980 average, from the NASA Goddard Institute of Space Studies, averaged by latitude. Note that there are data here for higher latitudes, since different data sources are used. Also, the time period is different. You can see that the temperature is rising much faster at the high northern latitudes than at the equator.

Figure 2. Departure of 2008 surface (~top 1 mm) temperature from 1951-1980 average, averaged at each latitude. From NASA/GISS.

Just as in the middle latitudes in Figure 1, the surface temperature trends in Antarctica (Figure 3) are complex, with some areas even cooling according to this plot. (Note there is an article on Antarctic warming in the 22 January issue of Nature magazine.)

Figure 3. Image of surface temperature change in Antarctica between 1981 and 2007. These are based on infrared radiation from the surface (upper 1 mm), obtained using National Oceanographic and Atmospheric Administration satellites. Since the data come from more than one satellite, carefully comparisons to “calibrate” the data to make a reasonably uniform record. The very strong warming (darker reds) around the coast often reflects replacement of ice by open water. For further information, see http://earthobservatory.nasa.gov/IOTD/view.php?id=8239.

Going back to Figure 2, imagine now averaging the temperature trend over the entire earth. Since all the numbers are positive, the temperature trend averaged over the entire earth will also be positive. A global average is the “warming” we normally refer to when talking (or writing) about “global warming.”

However, the climate is changing in other ways as well. Perhaps you have heard about the fact that more heavy rain events are possible, or that the water vapor content in the atmosphere is increasing along with the temperature. This is another reason to prefer the term “climate change.”

Figure 1. Map showing location of Boulder and CASES-99. The colors represent contours. The Rocky Mountains are yellow, orange, and red on this map. The colors denote elevation, with yellows, oranges and reds indicating higher terrain.

How does the air temperature relate to the surface temperatures that the students measured during Dr. C.’s field campaign? To answer this question, I looked at how the surface temperature related to the air temperature at our house.

The air temperature at our house was measured at 1-1.5 meters in our carport, and also on a thermometer I carried with me on our early-morning walk around the top of our mesa. That temperature, as noted above, was -21 degrees Celsius. To get the surface temperature, I put the thermometer I was carrying on the surface after I finished my walk. I am assuming that this temperature is close to the temperature that would be measured by a radiometer like the one used in GLOBE. I took the reading ten minutes later.

Just for fun, I also measured the temperature at the bottom of our snow (now 10 cm deep) and at the top of the last snow (about in the middle of the snow layer). At these two places, I put the snow back on top of the thermometer, waited ten minutes, and then uncovered the thermometer and read the temperature. The new snow was soft and fluffy, while the old snow was crusty; so it was easy to find the top of the old snow.

All of the measurements were taken close to sunrise, when the minimum temperature is normally reached, and the area where I took the measurements was in the shade.

Figure 2 shows the temperatures that I measured.

Figure 2. Temperature measurements at the snow surface, between the old and new snow, at the base of the snow layer, and at 1-1.5 meters above the surface at 7:30 in the morning, local time.

That is, the temperature was coolest right at the top of the snow. The temperature was warmer at the top of the old snow, and warmest at the base of the snow. As noted in earlier blogs, the snow keeps the ground warm.

The temperature at the top of the snow was also cooler than the air temperature. The surface temperature is often cooler than the air temperature in the morning, especially on cold, clear, snowy mornings like this one. However, on hot, clear, days in the summertime, the ground is warmer than the air.

Here are two sets of measurements taken in the Midwestern United States in October of 1999. Could you guess which measurements were taken at night, and which measurements were taken during the day even if the times weren’t on the labels? The first plot is from data taken after sunset, while the second plot was from data taken at noon.

Figure 3. Data from the 1999 Cooperative Atmosphere Exchange Study (CASES-99) program in the central United States, courtesy of J. Sun, NCAR.

In my last blog on birding, I took a picture of a blind on Saturday, 6 December (Figure 1). Early that morning, the temperature was cold (about -5 degrees Celsius) and the ground had about 12 centimeters of snow on the ground. The lakes near the blind were frozen when we arrived there around 9:30 a.m. local time. The temperature was probably still below freezing when I took the picture. The next morning, we woke up to 10 degree Celsius temperatures, and the 12 centimeters of snow we had in our yard had entirely disappeared. When we returned to the blind to record the how different things looked, it was 11:30 a.m. local time – about 26 hours later.

Figure 1. Picture of blind taken for last blog. Sawhill Ponds, Boulder, Colorado, 10:00 a.m. Local time. The snow was about 10 centimeters deep here; the lakes were frozen.

Figure 2. Picture of blind, roughly 26 hours later (11:30 Local Time, 7 December 2008). Note that not only has the snow disappeared, but the soil is dry in some places.

Basically the temperature didn’t fall much the night of 6 December – in fact it might have even warmed. This is because air is coming down from higher up in a Chinook. As air sinks in the atmosphere, it gets compressed (squashed) by having more air above it pressing down. This squashing warms the temperature – much as the temperature of the air in your bicycle tire warms when you pump (squeeze) more air into it. In sinking dry air, the temperature rises 10 degrees Celsius for each kilometer – quite a bit.

Figure 3 shows the temperature record for another Chinook (the instruments at NCAR Foothills Lab, which lies between where we live and Sawhill Ponds) weren’t working on 6-7 December, so I couldn’t get the data). The air is very dry during the Chinook. (The air is dry if the temperature is much higher than the dew point. Recall that fog or dew forms when the temperature and dew point are equal, so it makes sense that drier air has lower dew points). The dryness of the air is not surprising – the air is drier higher up. So the dryness is a sign that the air is coming from higher up.

Figure 3. Temperature and dew point from a Chinook on 11 February 2008, at roof level. From NCAR Foothills Laboratory in Boulder, Colorado. You can tell from the cooler temperatures starting around 15:00 local time that the Chinook ended about that time. From http://www.rap.ucar.edu/weather/.

You notice how the temperature went up half way between 23:40 (11:40 p.m.) and 02:40 (2:40 a.m.) local time and then didn’t change much for the rest of the night like it normally does? Also the temperature wasn’t going up much the next morning. (Note: 50 degrees Fahrenheit is about 10 degrees Celsius). During this time the wind was out of the west – from the mountains, meaning sinking air (Figure 4). Also notice that the temperature cools off when the wind changes from west to north at around 15:00 local time (3:00 p.m.).

Figure 4. As in Figure 3, but for wind direction

The lack of a temperature change makes me think that the air in Boulder didn’t just simply slide down the mountain, but we were getting air from above the surface. Air high above the ground doesn’t cool or warm as much as air right next to the ground does.

So we have four clues that the air came from higher up during the Chinook. First, the temperature rose to abnormally high levels at the onset of the Chinook and rapidly cooled afterward. Second, the wind came from the mountains to the west. Third, the air was very dry. And finally, the temperature didn’t change during the day like it normally does. The last clue also suggests the air came from above the surface.

What do the clouds look like? In a Chinook, the wind blowing across the mountains flows in ripples much like the water flows over rocks in a stream. It’s harder to see air flow than to see the water flow. However, clouds occur when the air is at the top of ripples, if the air is moist enough. From the surface here in Boulder, we saw a long line of low clouds stretching along the mountains (one ripple), and higher cloud doing the same thing, but farther east (Figure 5).

Figure 5. Clouds associated with the Chinook at 14:50 local time, looking northwest. The mountains are to the west. The cumulus clouds near the horizon are just to the east of the mountains, which are not visible on this picture. The higher clouds (altocumulus) are part of a broad north-south band starting east of the mountains. The little tail in the middle is the leftovers from a contrail. Looking eastward, I could see that the altocumulus clouds stretched to the horizon.

You can probably see this more clearly from space. First, I show you the visible image (Figure 6). You can see some ripples over the mountains, a dark area stretching from Boulder (plus sign) to the south, and the altocumulus (or higher) clouds extending east-south east from the dark area.

Figure 6. GOES satellite visible image of clouds at 2132 UTC (1432 Local Standard Time). The plus sign snows where Boulder is. Note the north-south clouds along the Rockies in the middle of Colorado (like ripples in the water). Then there is a broad band of clouds stretching eastward to the east side of Colorado. This is the larger-scale view of the altocumulus in Figure 5. From http://www.rap.ucar.edu/weather/satellite/.

We can see the difference in the heights of the “ripples” and the broad area of altocumulus clouds by looking at the image showing the infrared signal (Figure 7), which is related to the temperature the satellite “sees” – either at the surface or at the top of the clouds. Since the temperature in the atmosphere drops with height at these heights, this temperature can be used to estimate cloud top height. The brighter areas indicate higher cloud tops, so the broad band of clouds to the east of Boulder appear to be higher than the ripples, which are hard to see.

Figure 7. GOES satellite infrared image in and around Colorado at 2132 UTC (1432 local time). The plus sign shows where Boulder is. The broad bands of clouds are showing up much more than the ripples. Since lighter colors indicate higher clouds, this tells us that the broad area of clouds to the east is higher than the ripples – just as in the picture I took in Boulder. (But I’m not sure we can see the ripple in my picture on the satellite). From http://www.rap.ucar.edu/weather/satellite/.

What was the result of the Chinook? We already pointed out the much warmer temperatures, the complete melting of our snow (12 cm in our yard originally), and the melting of ice on many of the lakes.

This also affected the ducks in the lakes near the blind.

On 6 December, when we went out to photograph the blind, we could find no ducks on the frozen ponds – only Canada geese waddling on the ice. Also, there were almost no birds at the feeders in our back yard. We were surprised, because we thought they would be hungry in the cold weather.

On 7 December, when we got up, the feeders were full of birds. So were the trees: chickadees, pine siskins, sparrows, finches, juncos, and collared doves, were eating continuously, even when squirrels and cats (and in one case a deer with antlers) came by. Today, when we went back to Walden Ponds (north of the blind), we saw many ducks on the one pond that had thawed out most completely. And the ducks and geese were eating. My guess is that they were making up for yesterday. But – there is a mystery. Where were the ducks during the cold weather? What do you think?

Do you have names for winds where you live? Winds – particularly those that bring different weather – have names around the world. In Africa, the hot dry winds that come south from the Sahara are called Harmattans. In southern Europe, cold winds that come out of the mountains are called Boras and warm winds that come out of the mountains are called Foehns in Germany. However, we also use the word “foehn” to describe warm dry winds from the mountains in the United States. In South Africa, the warm winds coming from the mountains are called “berg winds,” since “berg” means mountain in Afrikaans. There is no snow to melt, but the berg winds do raise the temperature in winter.

In my last blog, I mentioned observing birds from a blind. What is a blind? It’s a structure that keeps the birds from seeing you. Usually, it’s made up of three walls and a roof, like the one I visit frequently here in Boulder (Figure 1). Blinds are built near places where you would expect birds. For example, there are often blinds near lakes, so that you can watch ducks. One nice thing about observing bird this way is that you can see them really well (you have to be very quiet, so you don’t scare the birds away), and you can photograph them. With the new electronic cameras, it doesn’t take much money to get and print nice pictures of birds.

Figure 1a. Blind at Sawhill Ponds, Boulder.

Figure 1b. View through one of the windows inside the blind.

Last week, we were birding at Palo Duro Canyon (marked by the + sign), which lies southeast of Amarillo, Texas (See Map in Figure 2).

Figure 2. Map showing Palo Duro Canyon, in the Texas Panhandle.

When we paid for going into the park, we were told that there was a blind near the Trading Post, where we could watch the birds. Of course there were many trails to walk on as well, but the blind was special, because we could watch the birds without disturbing them.

Here, the blind was near two bird feeders and an artificial stream where the birds could bathe. There was also a lot of nearby brush so that the birds had a place to escape to if they were frightened. For the humans, there are often benches to sit on inside the blind.

Here are some birds that we saw from the blind.

Figure 3. Fox Sparrow. This bird is about 18 cm long.

Figure 4. Northern Cardinal (22 cm long)

Figure 5. Goldfinch (13 cm long)

Figure 6. Pine Siskin (13 cm long) busily feeding.

Figure 7. White crowned sparrows

These pictures were taken with an ordinary digital camera with a zoom lens. Notice the brush in the background. You can take pictures, too – but avoid using your flash bulb. That will startle the birds. If it is too dark to get pictures without a flash bulb, just enjoy the birds and come back another day to take pictures.

It was fun to watch the birds interact with one another or with other animals. The Cardinal would chase the Goldfinches and Pine Siskins away. They would wait in the bushes until the Cardinal flew away, and then come back in and eat some more. This morning there were several Sparrows (I think) at our feeder here in Boulder this morning. They would take turns eating thistle seed – until a squirrel frightened them away.

Of course we saw birds while hiking at Palo Duro Canyon, but it’s hard to get close enough to photograph them without scaring them away – and we didn’t want to do that. But there was one kind of bird big enough to photograph from a distance – the Wild Turkey (Figure 8). Figure 8 is a bit blurrier than the others because it was taken in dim light and I didn’t have a tripod.

Figure 8. Wild Turkeys (Males are 46 cm long; females 37 cm.)

How do I know what birds these are? Some I learned a long time ago. But when I see a new bird, I look at a field guide with pictures of birds. Or I take notes on what the bird looks like and the way the bird behaves. Is it wagging its tail? Does it fly around a lot? Does it feed on the ground? Does it like to be high up in the trees? How big is it (it helps to have other birds you know nearby for scale, but this doesn’t always happen). Does it eat berries? What is the shape of its bill? Then, when I get home, I can either look at a bird book or find information about the birds on the Web. For a really nice introduction to identifying birds, a very helpful site is All About Birds, and of course there is some really nice information on hummingbirds at the Operation Rubythroat website.

You can have a “blind” at home. Look for a place for a bird feeder outside a window. If there are trees or bushes nearby, the birds have a place to go if they get startled. Look on the web (including the web site sited last time) for how you can make your yard comfortable for birds.

Once you know a few common birds for your area, you can watch for their arrival in the spring or fall. Common birds are probably easiest to use to indicate seasons, since your chances of seeing them are better. In the meantime, enjoy the winter birds!

Today I am blogging from San Francisco, California. I am attending the American Geophysical Union (AGU) meeting in San Francisco, California. It is a meeting that I try to come to every year. AGU is a professional organization made up of scientists who study the Earth and our solar system.

A conference like this one is a way for scientists to share information. The picture below shows how the scientists show each other the research they have performed. You might be thinking, “Dr. C, that looks a lot like a science fair that my school has.” You would be right. Poster presentations are very similar to science fair projects that students do.

Figure 1. Poster session at the AGU meeting.

Coming to the AGU meeting gives me a chance to see my scientist friends. My friend Claudia Alexander is the lead scientist on the Casini-Huygen project and Rosetta mission for NASA. The Casini-Huygen project is a satellite that is studying Saturn and its moon Titan. The Rosetta mission is going to study what makes up comets.

I presented a poster on an Earth System Science education course that I teach. Teachers take the course to continue their learning. You may have not known that either. Below is a picture of Gary Popiolkowski. He is a seventh and eighth grade science teacher at Chartiers-Houston Jr./Sr. High School in Houston, Pennsylvania. His students made the poster for him. It is a great poster as you can see from the picture. He mentioned to me how proud he was of his students for designing and making the poster.

Figure 2. Teacher Gary Popiolkowski

Figure 3. It’s me, Dr. C in front of my poster at AGU.

Dr. C