Plants Dance to the Rhythms of the Ocean


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If you watched a movie of the Earth’s climate history, you would see the ocean frequently plays the role of leading actor. If you observed sea surface temperature across the entire globe, over a span of years you would begin to detect patterns. Of course, since you cannot see heat, you would have to assign colors to represent temperature. What would become immediately obvious to your eye is that the temperature anomalies of El Niño and La Niña occur roughly every 3 to 7 years. These would appear as vast red and blue spikes, respectively, appearing off the west coast of South America and extending westward along the equator across most of the Pacific Ocean.

Watching the movie a little longer, your eye might pick up the fact that there is a long-distance relationship between the equatorial Pacific and the equatorial Atlantic Oceans. Interestingly, and for reasons scientists don’t fully understand, when the southern Pacific is warmer than average the southern Atlantic is cooler than average, and vice versa. These temperature patterns swing back and forth between the two oceans like a pendulum. You might also notice that there is an oscillation in the Northern and Southern Atlantic Ocean, on either side of the equator. One side is cooler than average for a year or two while the other side is warmer than average, then they flip-flop and this pattern continues.

If you watched for a decade or longer, many more recurring patterns would begin to reveal themselves. For instance, you would see that the body of water that extends from the western equatorial Pacific into the eastern Indian Ocean, called the Indo-Pacific warm pool, seems to pulsate. That is, the warm pool expands and contracts in size while its average annual temperatures rise and fall over cycles of about two decades.

The movie has a surprise ending. Perhaps you didn’t notice, but there was another actor onscreen—on the land. Turn your attention to the continents and you will see green waves of vigorous plant growth and creeping brown hues of drought wax and wane across the landscapes as if the world’s vegetation dances in response to the rhythms of the ocean. How can this be? Is there a connection?

Yes, say a team of scientists at NASA’s Goddard Space Flight Center. Led by Sietse Los, terrestrial biologist, the team recently assembled the first long-term global data set that demonstrates there is a connection between changing patterns of sea surface temperature and patterns of plant growth across the Earth’s landscapes. The results of their new study appeared in the April 2001 issue of the Journal of Climate (Los et al. 2001).

next A New Look at an Old Data Set

  images of January SST and NDVI

The above series of images shows changes in sea surface temperature and land plant growth in every January from 1983 to 1989. In the ocean, blue indicates where temperatures are cooler than normal and red is warmer than normal; on land, yellow indicates less vigorous than normal vegetation growth and green shows more vigorous growth than normal. As sea surface temperatures rise and fall, the vegetation in adjacent areas responds. In general, cool ocean water upwind leads to drought and reduced vegetation growth, while warm ocean waters produce excess rainfall and vigorous plant growth. Notice how the vegetation in northern South America responds to water temperatures in the Atlantic Ocean. The corresponding animation shows the effect dramatically.

Images courtesy Marit Jentoft-Nilsen, NASA GSFC Visualization and Analysis Lab, based on data from Sietse Los, University of Wales.


Once the movie loads and begins playing you may click anywhere on it to stop it. Use your keyboard arrows to manually move forward and backward through the animation at a controlled rate. Double click on the movie to play it again at its normal rate.

Click to download the high quality animation (26 MB).

Back to Watching Plants Dance to the Rhythms of the Ocean


A New Look at an Old Data Set

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Sietse Los received his PhD in Earth Sciences from the Free University in Amsterdam. His research focus is on land vegetation and the roles that terrestrial plants play in the global water and carbon cycles. When he came to NASA’s Goddard Space Flight Center in 1989, he was looking for ways to analyze multi-spectral data on vegetation in three dimensions—both through time and space. While attending a summer conference at Goddard organized for visiting scientists, Los saw a presentation by a colleague who showed a movie of sea surface temperature together with precipitation patterns. Clearly, the movie showed that temperature anomalies like El Niño exert a profound influence on rainfall patterns around the globe.

But why stop there? Why not go a step farther and see if there is a relationship between sea surface temperature and plant growth? Los decided to do just that.

Back at Goddard, Los approached colleagues James Collatz, Compton Tucker, Lahouari Bounoua, and Piers Sellers to help him reprocess and analyze remote-sensing data collected by NOAA’s Advanced Very High Resolution Radiometer (AVHRR). This would seem to be the perfect data set since NOAA AVHRR sensors have been collecting global-scale data since the early 1980s. But, according to Los, there were problems with the data.

"AVHRR was never designed for vegetation monitoring," Los states. "It was designed mainly for monitoring the atmosphere (i.e., weather patterns, cloud cover, and air temperature) as well as measuring sea surface temperature and observing the extent of snow and ice on the surface."

Los explains that the AVHRR missions did not have the stringent calibration and orbital requirements that today’s Earth observing satellite missions have. Some of the NOAA AVHRR missions are known to have drifted by as much as 4 hours in their orbits, which changed the times of their equatorial crossings. (An extreme example is NOAA-9, which started as an afternoon satellite. It was replaced by NOAA-11, but was turned on again when NOAA-11 failed. By that time NOAA-9 had become a morning satellite.) In turn, this means that the relative angle of the sun would differ at the time data were collected over a given location, which has an impact on the data. "What you observe on the surface changes as a function of the sun’s angle of illumination," Los says.


NOAA POES Satellite
The image above shows one of the NOAA Polar Orbiting Environmental Satellites that carries the Advanced Very High Resolution Radiometer (AVHRR) instruments. The AVHRR has been collecting the data used to measure vegetation and sea surface temperature since 1978. Long-term monitoring is an essential part of studying climate trends. New instruments such as the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Global Land Imager (GLI) will extend and improve on AVHRR’s heritage.

Image courtesy NASA GSFC


Solar Zenith Angle Comparison

Moreover, the performance of all satellite sensors degrades over time. They experience extreme temperature shifts, bombardment from cosmic and microwave radiation, possible impacts from micrometeorites, and corrosive outgassing from the satellite itself. Without adequate onboard calibrators, it is difficult to quantify how sensors change over time. "You sometimes see the sensitivity of the sensor changes over time," Los observes. "The AVHRR aboard NOAA-9, for instance, measured different amounts of vegetation on the surface over time. And its measurements differed from observations made by the AVHRR aboard NOAA-11."

James Collatz adds that AVHRR does not have the spectral sensitivity of more modern remote sensors like the Moderate-resolution Imaging Spectroradiometer (MODIS) flying aboard NASA’s Terra spacecraft. Whereas, AVHRR is sensitive in only 5 channels of the spectrum, MODIS has 36 channels, thus providing much finer multi-spectral detail. Consequently, in reprocessing the AVHRR data set, the team had to painstakingly fine-tune the data to correct for atmospheric effects that could interfere with its measurements, such as aerosol particles in the atmosphere that scatter sunlight and thus weaken the signal from the surface. Such atmospheric corrections are far easier with sensors like MODIS.


The angle between the sun and the Earth’s surface, called solar-zenith angle, changes reflected sunlight in several ways. At low solar zenith angles, such as local noon, top, the sunlight passes through relatively little atmosphere, minimizing scattering of light by the atmosphere and any effects of pollution, haze, or water vapor. The sunlight is also perpendicular to the Earth’s surface, so it is scattered directly back towards a sensor.

At high solar-zenith angles, like the bottom image (55°), atmospheric scattering is increased, decreasing the amount of shorter wavelength light (blue) in incident sunlight. Some surfaces reflect light differently at high angles than low ones. An additional effect is the increase in the apparent depth of forest canopy at high angles.

Images by Robert Simmon, NASA GSFC


Difference in Calibrated and Uncalibrated NDVI Data

The team took all of the above factors into consideration as they reprocessed the AVHRR data set. Their objective was to "correct" the data so as to remove any artifacts that may have erroneously been introduced into the data so they could be sure that what they were seeing was the signal of reflected sunlight and emitted thermal infrared energy from the surface. Once they confirmed the reprocessed data set gave them a clearer picture of global plant growth, they were ready to begin their analysis.

"Using various analysis techniques, we can now extract signals from the vegetation data that relate to the climate system," Los states. "And we can now correlate vegetative response to climate change in three dimensions—through time and space."

next When Plants are Thriving
next Watching Plants Dance to the Rhythms of the Ocean


The two images at left show the difference between uncalibrated (top) and calibrated AVHRR vegetation data in West Africa. Notice that the density of green foliage (defined as Normalized Difference Vegetation Index, or NDVI) is greater in the calibrated NDVI data. Errors in the data can either raise or lower measured vegetation index values.

Images courtesy Dan Slayback, NASA GSFC Laboratory for Terrestrial Physics.


When Plants are Thriving

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When it is thriving, land vegetation can absorb vast amounts of carbon dioxide from the atmosphere through the process of photosynthesis. Over a period ranging from months to decades, however, the carbon stored in plants is released back into the atmosphere through the processes of respiration, decomposition, and fires, thus completing the carbon cycle. With their new data set, the team wanted to gain new insights into where there are large variations in plant growth because such variations have implications for where and when vegetation serves as a source for carbon dioxide (releasing it into the atmosphere) and when it is a sink (or absorbing it). Additionally, they wanted to find out how these sources and sinks change over time. Seasonal variations in plant growth can be quite large, and plant growth can vary widely from one year to the next. Moreover, recent studies suggest that, due to global warming, the growing season is getting longer at higher latitudes, thereby increasing the ability of terrestrial plants to serve as a carbon sink (Myneni et al. 1997).

  Read "Measuring Vegetation (NDVI & EVI)" to learn how scientists use satellite data to monitor vegetation growth.

Carbon Cycle Illustration

To determine where and when plants are thriving, the team used AVHRR to measure Normalized Difference Vegetation Index (NDVI), which is basically an indication of how green a patch of land is. To derive NDVI, researchers must observe the distinct colors (wavelengths) of visible and near-infrared sunlight reflected by plants. As can be seen through a prism, many different wavelengths make up the spectrum of sunlight. When sunlight strikes an object, certain wavelengths of this spectrum are absorbed and other wavelengths are reflected. The pigment in plant leaves—chlorophyll—strongly absorbs visible light (from 0.4 to 0.7 µm) for use in photosynthesis. The cell structure of the leaves, on the other hand, strongly reflects near-infrared light (from 0.7 to 1.1 µm). The more leaves a plant has, the more these wavelengths of light are reflected and absorbed, respectively. (Click for more details on NDVI.)

Los' team processed eighteen years of AVHRR data into a series of one-month global composite images of NDVI. From there, they were able to calculate the average greenness value for a given patch of land for a particular time of the year. Any significant departure from the average greenness value would then be an anomaly. Similarly, they used AVHRR data to calculate average global sea surface temperatures for any given patch of ocean for every month over the same 18-year time period. Again, any significant departure from average is termed an anomaly.

When they put the two sets of measurements together into one continuous movie, Los' theory was confirmed—there is a clear and obvious relationship between sea surface temperature trends and terrestrial plant growth across the continents. "For the first time, we can see patterns of climate variability reflected in land vegetation growth, globally, which was not possible before," Los states. "Until now, we haven't had a good data set to show us how vegetation changes over long periods of time."

next The Global Heat Engine
next A New Look at an Old Data Set


Carbon atoms move from the atmosphere to the biosphere (plant and animal life) and the lithosphere (the solid Earth) in a cycle that spans from months to decades. Plants "breathe" carbon dioxide, using the carbon to grow. When a plant dies (or its leaves fall off) the carbon dioxide is released back into the air as the organic material decays. Alternatively, the carbon may be buried and eventually become peat, coal, or oil.

Image by Robert Simmon, NASA GSFC


The Global Heat Engine

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When viewing the 216 monthly false-color images consecutively in a time-series animation, distinct large-scale patterns of change become quickly obvious to the eye. The relationship between sea surface temperature and plant productivity becomes apparent too. Reds representing unusually warm waters wax and wane across patches of ocean while the greens of vigorous plant growth, or the browns of drought, roll across landscapes in response.


El Nino and La Nina


Collatz points to the recurring cycles of the El Niño-Southern Oscillation in the equatorial Pacific and Southern Atlantic during the 1980s. Then he notes the subsequent patterns of drought and then vigorous growth that sweep back and forth across South America, as if the continent were the ball in an ongoing ping-pong match between the two mighty oceans.

"What it shows is what you might expect," he observes. "Sea surface temperatures have an impact on the climate (temperature and precipitation) over land and this affects growth of vegetation."


A very strong El Niño brought drought to northern South America in 1983, while a large La Niña brought excess rain in 1989. The vegetation responded by growing poorly in 1983 and vigorously in 1989.

Image by Marit Jentoft-Nilsen, NASA GSFC Visualization and Analysis Lab, based on data from Sietse Los, University of Wales.


QuikSCAT wind data

Dubbed the "global heat engine," Earth scientists have long since recognized that as the ocean releases warmth and moisture into the overlying atmosphere it dramatically influences weather patterns. Anomalously high sea surface temperature, as seen in the equatorial Pacific during El Niño, can drive weather patterns to extremes–producing torrential rains and flooding in some parts of the world and severe drought in others.

But, says Collatz, you cannot expect El Niño to always have the same effects on plant growth across a given region. The impacts of some El Niños are more intense than others.

"Climate oscillations can sometimes interact with one another," explains Collatz. "For instance, the effects of El Niño are sometimes magnified and at other times almost completely cancelled out by the North Atlantic Oscillation (NAO)." (The NAO is an ongoing, long-distance relationship between a high-pressure system over the Azores Islands and a low-pressure system over Iceland. For more details, read Searching for Atlantic Rhythms.)


Trade winds blow from east to west along the equator, carrrying moisture over South America. Evaporation is slowed if the sea surface is cooler than normal, leading to decreased rainfall over adjacent land. Conversely, more evaporation leads to excess rainfall when the sea surface temperature is higher than normal. The image at left shows winds over the Atlantic on June 3, 2001. Arrows correspond to direction, color to velocity.

Image courtesy Seaflux, NASA Jet Propulsion Lab.

Graph of Effects of ENSO and NAO on Brazil

Ultimately, say the authors, this new data set strengthens scientists’ ability to forecast the effects of climate change on vegetation on a global scale. But in order to improve their predictions of what impacts El Niño might have, they need to know what other climate oscillations might affect the strength of El Niño.

"Natural resources, food—lots of things depend upon the healthy growth of vegetation," concludes Collatz. "It is important for us to understand and be able to predict how forests and crops will respond to climate cycles like El Niño."

Toward that objective, the team now has almost 20 years of global observations to give scientists a perspective they’ve never had before. With these new data the team can begin to examine in more detail the roles of the terrestrial biosphere in both the carbon and water cycles.

Collatz adds that the team is already looking ahead to the new NASA satellite sensors now in orbit that are much better calibrated than AVHRR, and they are specifically designed to measure the Earth’s vegetation. Even as they improve upon the quality of the measurements, these sensors—such as the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), flying aboard OrbView-2, and the Moderate-resolution Imaging Spectroradiometer (MODIS), flying aboard Terra—will extend the heritage of the AVHRR data set well into the new millennium.

  • References
  • Los, Sietse O., G. James Collatz, L. Bounoua, P.J. Sellers, and C.J. Tucker, 2001: "Global interannual variations in sea surface temperature and land surface vegetation, air temperature and precipitation." Journal of Climate, Vol. 14, pp. 1535-1549
  • Myneni, Ranga B., C.D. Keeling, C.J. Tucker, G. Asrar, and R.R. Nemani, 1997: "Increased plant growth in the northern high latitudes from 1981-1991." Nature, Vol. 386, pp. 698-702.

next When Plants are Thriving


Climate cycles—such as El Niño/Southern Oscillation (ENSO) and the North Atlantic Oscillations (NAO) can act in concert, amplifying their effects, or against each other, limiting their effects. This graph shows precipitation anomaly in the area surrounding Nordeste, Brazil. In 1985 the NAO and ENSO both contributed extra rainfall to the region. In 1989 La Niña again brought extra rain to Brazil, but the effects of the NAO reduced the total amount of rainfall.

Graph by Robert Simmon, based on data provided by Sietse Los, University of Wales.

  Will Runaway Water Warm the World?

It was hot. Hotter than any record in the books. Instead of photographing picturesque fountains in the towns of southern France, tourists were soaking in them. In London, trains sat quietly in the stations; officials were too afraid that the metal tracks would buckle to allow a speeding engine to race over them. Sparked by hot, dry conditions, wildfires raged across France, Spain, Portugal, and Italy. Swiss mountain glaciers thinned more than any other year in the past decade. The doomsday-like heat wave that engulfed Europe in July and August 2003 also carried a darker toll. In France alone, 14,802 more people died that August than in the same month the previous year; for all of Europe, the unofficial death toll reported in the media soared to 19,000. Were these unusually high temperatures—up to ten degrees Celsius hotter than 2001—a result of global warming? It’s not clear, but some fear that the summer’s heat may be an ominous harbinger of some future climate.

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  Rhone Glacier

Across the globe, temperatures are slowly creeping up. According to the U.S. National Climatic Data Center, the global average surface temperature has gone up 0.4 degrees Celsius (plus or minus 0.1 degree) in the past 25 years alone. While the extra heat may not have you sweating yet, larger increases are predicted, and that has some people tugging at their collars. The Intergovernmental Panel on Climate Change, a policy advisory group made up of members of the World Meteorological Organization and the United Nations Environment Programme, estimates that the average global surface temperature could climb anywhere from 1.4 to 5.8 degrees Celsius by the year 2100.


Once a thick tongue of ice that poured into the Gletsch valley (inset), the Rhone Glacier has shrunk dramatically since 1850. In 2003, the Rhone Glacier and other Swiss glaciers retreated more than any other year since scientists began taking measurements in the 1800s. While the summer’s extreme temperatures caused the glaciers to thin more than usual, scientists say that the glaciers retreated in response to long-term warming. (Photograph copyright, inset courtesy Library of Congress)

Graph of Predicted Temperature Rise

Part of the reason the predicted temperature range is so great is that scientists don’t entirely understand whether the atmosphere will become more humid as it warms, and humidity is one of the primary factors that will influence how much the climate will warm over the next century. If the humidity of the atmosphere does indeed increase, it can as much as double the warming from carbon dioxide alone. Thus, an understanding of how the humidity of the atmosphere will change is of fundamental importance in predicting future climate. The problem is one that Ken Minschwaner and Andrew Dessler, researchers at NASA Goddard Space Flight Center, have worked to remedy using data from the Upper Atmosphere Research Satellite (UARS).


Predictions of warming in the next 100 years vary by about 5 degrees Celsius, from a low of 1.4 degrees to a high of 5.6 degrees. The wide variation is due in part to uncertainty in the magnitude of the feedback between warming and increased rates of evaporation. In this graph, dark green areas represent predictions based on the averaged results of multiple climate models, while light green areas represent the predictions of single climate models. (Graph adapted from Climate Change 2001: The Scientific Basis)

  Artist's Rendering of UARS

Minschwaner, also a Professor of Physics at the New Mexico Institute of Mining and Technology, and Dessler, also a researcher with the University of Maryland’s Earth System Science Interdisciplinary Center, formulated a simple, one-dimensional model to describe how the humidity of the atmosphere will change as the Earth heats up in response to carbon dioxide emissions from burning of fossil fuels. Surprisingly, their model predicted smaller increases in humidity in the upper atmosphere than large global climate models do, and data collected by the Microwave Limb Sounder and the Halogen Occultation Experiment on NASA’s UARS satellite support their model. Their findings imply that the Earth will warm significantly, but probably not as much as most global climate models predict. Their results appeared in the Journal of Climate on March 15, 2004.


Using instruments aboard NASA’s Upper Atmosphere Research Satellite (UARS), scientists measured humidity high in the atmosphere. The researchers then compared those humidity measurements with sea surface temperature records. Using these observations, the researchers quantified the feedback between rising temperatures and increasing concentrations of water vapor in the atmosphere. This crucial variable in climate change estimates had previously been based on speculation and modelling, but not direct observations. (Rendering by Jesse Allen, NASA GSFC)