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Earth Observations from Space: The First 50 Years of Scientific Achievements
3
Weather
Because many aspects of daily life are affected by the weather, understanding and predicting the weather has been a human quest for millennia. Space-based observations have played pivotal roles in the history of weather forecasting. Their contributions to forecasting at all spatial scales can be grouped into three areas, which are described in this chapter: weather imagery, atmospheric properties, and numerical weather forecasting.
Fundamentally, weather forecasting is a four-dimensional problem, involving three spatial dimensions and time. The air that is now affecting point B was yesterday at point A and tomorrow will be at point C. Similarly, the storm system centered at point A yesterday is centered at point B today and has a different shape, size, and intensity than it did yesterday. To forecast tomorrow’s weather at a point, one must know today’s weather over a broad region surrounding that point. The farther one wants to forecast into the future, the larger the area must be where one knows the weather today.
In 1846 the state of the art in weather forecasting was succinctly stated by François Arago1: “Whatever may be the progress of sciences, NEVER will observers who are trustworthy, and careful of their reputation, venture to foretell the state of the weather.” In the United States, however, isolated observers were communicating among themselves to understand the horizontal extent of the weather, but they communicated by mail, which meant that the weather could not be forecasted, only understood in retrospect.2 With the development of the telegraph, Joseph Henry3 and James Espy4 experimented with transmitting weather observations in real time to a central site, where weather maps could be drawn and forecasts made. By 1870, President Ulysses S. Grant signed a joint resolution of Congress authorizing the Secretary of War to establish a “Division of Telegrams and Reports for the Benefit of Commerce” as part of the U.S. Army Signal Service Corp (NWS 2006). This division became the Weather Bureau in 1890 and the National Weather Service in 1967.
The development of radiosondes (weather balloons that transmit information to a fixed location) in the 1930s yielded measurements that resulted in major advances in weather forecasting by adding the crucial vertical dimension to meteorological observations. About half of the stations in the Integrated Global Radiosonde Archive depicted in Figure 3.1 make observations twice per day. Though numerous, these stations cannot give the desired global picture of the current state of the weather. The ocean is especially data sparse.
After World War II, rockets were sufficiently advanced to be able to lift cameras high above the clouds to take photographs of weather systems and to indicate the potential for weather observations by Earth-orbiting satellites. This led Harry Wexler5 to publish a paper in 1954—3 years before the launch of the first satellite and 6 years before the Television Infrared Observation Satellite (TIROS) (see Chapter 2)—titled “Observing the Weather from a Satellite Vehicle” (Wexler 1954). Thus, weather observations from space were not serendipitous but were eagerly anticipated.
Since the beginning of the space age, perhaps 200 weather satellites have been launched, as nations around the world recognized their value and as technology advanced to make more capable instruments possible.
WEATHER IMAGERY
The first weather satellites attempted simply to “take pictures” from space. By the mid-1960s, engineers had
1
1786-1853, director of the Paris Observatory and permanent secretary of the French Academy of Sciences.
2
For a history of these developments, see Fleming (1990).
3
1797-1878, first secretary of the Smithsonian Institution and one of the founding members of the National Academy of Sciences.
4
1785-1860, America’s first national meteorologist.
5
1911-1962, chief of the Scientific Services Division of the Weather Bureau.
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Earth Observations from Space: The First 50 Years of Scientific Achievements
FIGURE 3.1 Locations of Integrated Global Radiosonde Archive stations. SOURCE: Data from the National Climatic Data Center, Durre et al. (2006). Reprinted with permission from the American Meteorological Society, copyright 2006.
developed the capability to fly satellites in sun-synchronous orbits,6 in which an instrument on a single satellite could view the entire Earth twice per day, once in daylight and once at night (Figure 3.2). Then meteorologists could tile the pictures together to form the long-sought global picture of Earth’s weather (Figure 3.3).
Also during the mid-1960s, the first geostationary satellites were launched. These satellites orbit Earth in the equatorial plane at the same angular velocity that Earth rotates on its axis; thus, they stay “stationary” over the same point on the equator. Although they do not view the entire Earth but only one hemisphere (Figure 3.4), they can make images frequently, not just twice per day. These images can be assembled into movies that allow forecasters to watch the weather in motion. This is an invaluable tool for weather analysis and forecasting (Box 3.1). Geostationary satellites rapidly became the choice of weather services worldwide, such that today they form a ring around the equator, providing coverage of the entire tropics and midlatitudes.
Many accomplishments in weather forecasting have been achieved using the imagery from weather satellites. Only a few can be mentioned in this document. Perhaps the most dramatic accomplishments relate to observing and predicting hurricanes and tropical storms. In 1900 a “surprise” hurricane roared out of the Gulf of Mexico over Galveston Island killing at least 8,000 people; it was the largest natural disaster in the United States (Blake et al. 2006). Since then an important scientific accomplishment occurred sometime in
FIGURE 3.2 One day’s orbits of a sun-synchronous satellite. A single instrument views the entire Earth. SOURCE: Kidder and Vonder Haar (1995). Copyright Elsevier, 1995.
the 1960s: with the continuous monitoring of weather by satellites, no tropical cyclone anywhere on Earth escapes detection (Figure 3.5). Indeed, Robert C. Sheets, former director of the National Hurricane Center (NHC), has written:
6
A circular, near-polar orbit in which the orbital plane keeps a constant relationship to the Sun-Earth line, such that the satellite passes over a point on the Earth near the same time every day.
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Earth Observations from Space: The First 50 Years of Scientific Achievements
FIGURE 3.3 First complete view of the world’s weather, photographed by TIROS 9, February 13, 1965. Image assembled from 450 individual photographs. SOURCE: Publication of the National Oceanic and Atmospheric Administration (NOAA), NOAA Central Library.
FIGURE 3.4 Example of the hemispheric coverage of a geostationary satellite. Taken by NASA’s Applications Technology Satellite 3 (ATS 3) at 1402 UTC on July 21, 1970. Note that Tropical Storm Becky can be seen in the Gulf of Mexico near Florida. SOURCE: NOAA Photo Library.
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Earth Observations from Space: The First 50 Years of Scientific Achievements
BOX 3.1
Weather “Movies”
One of the best ways to understand the impact that observations from space have had on weather forecasting is to watch the weather in motion in a sequence of satellite images. Unfortunately, this is impossible in a printed document. Readers are urged to visit one of the many Internet sites that offer satellite movies and try a bit of “nowcasting”: Where is that storm going, and when will it arrive at the reader’s location? Here are a few sites:
NOAA’s Geostationary Operational Environmental Satellites (GOES) site: http://www.goes.noaa.gov (click on the MPEG or Java Applet icon)
Japan Meteorological Agency’s Multi-functional Transport Satellite (MTSAT) site: http://www.jma.go.jp/en/gms/
EUMETSAT’s Meteosat site: http://www.eumetsat.int (under “Image Gallery” choose “Real-time Images”)
The greatest single advancement in observing tools for tropical meteorology was unquestionably the advent of the geosynchronous satellite. If there was a choice of only one observing tool for use in meeting the responsibilities of the NHC, the author would clearly choose the geosynchronous satellite. (Sheets 1990)
From these observations we learned that tropical cyclones go through a life cycle that can be recognized and categorized in satellite imagery. The Dvorak scheme (Dvorak 1975) for estimating the intensity of tropical cyclones, which ranks storms between 1 and 8 based on wind speed and other features, is used worldwide. Tropical cyclone studies have benefited tremendously from satellite data (e.g., Special Sensor Microwave/Images, Advanced Microwave Sounding Unit, and QuickScat), which have been used to develop algorithms for monitoring and predicting hurricane intensity, tracks, and wind structures (Kidder et al. 1980, Demuth et al. 2000).
Since the advent of satellite imagery, scientists have learned to remotely identify many previously known weather features: fronts, high- and low-pressure systems, fog, low clouds, cirrus, and thunderstorms (Bader et al. 1995). Satellite observations also led to the discovery of thunderstorm clusters, called mesoscale convective complexes, which are unrelated to classical storm systems (Maddox 1980). Scientists also learned that rain-cooled air from thunderstorms descends and spreads out at the ground, producing an outflow boundary. When this boundary interacts with an adjacent storm, the intensity and destructive potential of both storms is amplified (Purdom 1976, 1986). In addition, satellite images revealed that a cold, V-shaped structure in the anvil of a thunderstorm is a signature of severe weather (Fujita 1978). It was also discovered that atmospheric turbulence is signaled by cloud patterns in the lee of mountain ranges (Ellrod 1989). Data from weather satellites allowed scientists to identify and forecast many other atmospheric phenomena too numerous to mention here (Kidder and Vonder Haar 1995).
ATMOSPHERIC PROPERTIES
In addition to taking pictures from space, satellites have allowed scientists to make radiometric measurements of the electromagnetic spectrum, from the ultraviolet to the microwave regions. From these measurements, scientists are able to retrieve properties of the atmosphere that are important to forecasters, especially the vertical temperature structure, winds, and moisture content (see Chapters 4 and 5), which are essential for numerical weather prediction.
Temperature profiles can be retrieved by several means. Given measurements at several wavelengths near an absorption band of a well-mixed gas, such as the 15-μm band of carbon dioxide or the 5-mm band of oxygen,, the radiative transfer equation can be used to retrieve a temperature versus height profile that is consistent with the measured radiances (Chahine 1968, Smith 1970; see also Box 5.2). This has been done with a large number of satellite instruments starting with the Satellite Infrared Spectrometer (SIRS) and the Infrared Interferometer Spectrometer (IRIS), both launched on the Nimbus 3 satellite on April 14, 1969. Recently, the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite (launched May 4, 2002) has provided high vertical resolution soundings using an infrared instrument that measures atmospheric radiation at 2,378 wavelengths (Chahine et al. 2006).
Radio occultation provides another way to measure atmospheric temperature profiles. Radio signals from Global Positioning System (GPS) satellites are refracted (bent) as they pass through the atmosphere. This bending angle can be measured from a second satellite. A sequence of refraction angles are measured as the GPS satellite rises or sets through the atmosphere. These measurements can be converted into a vertical profile of index of refraction of the atmosphere and thus into a vertical temperature sounding with high vertical resolution (Ware et al. 1996). The first such instrument, GPS/MET, was launched on the MicroLab 1 satellite on April 3, 1995; a constellation of six satellites (Formosa Satellite [FORMOSAT-3]/Constellation Observing System for Meteorology, Ionosphere, and Climate [COSMIC]) was launched on April 14, 2007.
A second property of the atmosphere that is necessary for weather forecasting is its water vapor content. It can be
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FIGURE 3.5 At 1745 UTC on August 28, 2005, Hurricane Katrina was observed by the Geostationary Operational Environmental Satellite (GOES 12) near the time of its maximum wind speed, 150 knots (173 miles per hour). SOURCE: National Hurricane Center. Reprinted with permission from the National Hurricane Center, copyright 2005.
retrieved from satellite measurements by some of the same methods that are used to retrieve atmospheric temperature (e.g., Weng et al. 2003; see also Box 5.2). Figure 3.6 is an example of the vertically integrated water vapor content of the atmosphere over the ocean measured through clouds in the microwave portion of the spectrum. These images are used by forecasters to monitor tongues of moisture from the tropical oceans that can cause heavy rain and flooding when they encounter land.
Winds, or the atmospheric flow field, must be known to forecast the weather. Scatterometers, such as QuikScat (launched June 20, 1999), which measure wind speed and direction near the ocean surface and have “revolutionized the analysis and short-term forecasting of winds over the oceans at NOAA’s Ocean Prediction Center” (Von Ahn et al. 2006), are discussed in Chapter 8. Another way to measure winds is to track clouds in sequences of satellite imagery, usually geostationary imagery. Small clouds travel with the wind. By observing the location of the same cloud in two successive satellite images and knowing the time difference between the images, the wind speed and direction can be calculated (Hubert and Whitney 1971). Figure 3.7 shows an example of the winds obtained by tracking clouds.
Finally, there are several other atmospheric parameters retrieved from satellite data that are useful to forecasters and are beginning to be used in numerical weather prediction models. For example, wind speeds around tropical cyclones are important for mariners and emergency managers. They are estimated by the Dvorak technique (mentioned above) and also by using microwave soundings. Microwaves penetrate the clouds and allow measurement of the magnitude of the warm core of tropical storms and its radial gradient, from which wind speeds can be derived (Kidder et al. 1980, Demuth et al. 2004).
Precipitation is a fundamental part of the hydrologic cycle and is further discussed in Chapter 6; it is often one of the first concerns when people think about the weather. Many satellite techniques have been developed to estimate rainfall (see, e.g., Barrett and Martin 1981). Today, daily rainfall estimates are available worldwide on the Internet. The
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most advanced precipitation estimation is from the Tropical Rainfall Measuring Mission (TRMM) satellite, launched on November 27, 1997 (Simpson et al. 1988, 1996). A joint U.S.-Japan mission, TRMM carries passive sensors of the visible to the microwave portion of the spectrum and is the first precipitation radar in space. Many other satellite-derived parameters are important to forecasters, including cloud height, cloud top temperature, and cloud phase; fog, smoke, and aerosol identification; and skin surface temperature (see, e.g., Kidder and Vonder Haar 1995).
NUMERICAL WEATHER PREDICTION
There are several reasons why Arago was wrong in 1846 and why today weather can be forecasted as much as 10 days ahead:
The discovery of the mathematical principles that govern atmospheric flow and the change of phase of water,
The invention of computers and the numerical techniques with which to solve these equations, and
The development of observing systems to supply the needed initial state of the atmosphere.
Without doubt, one of the chief reasons for the success of weather forecasting is that Earth-orbiting satellites provide an accurate global initial atmospheric state, which the numerical weather prediction models project into the future. Today, satellite data constitute the vast majority of the data available for the initialization of numerical weather prediction models and has the greatest impact of any measuring technology in improving forecast skill. Table 3.1 lists the satellite data currently used to initialize models run by NOAA’s National Centers for Environmental Prediction (NCEP).
FIGURE 3.6 Vertically integrated water content of the atmosphere (in kilograms per square meter) derived from microwave measurements on six sun-synchronous satellites, three NOAA satellites, and three Defense Meteorological Satellite Program (DMSP) satellites. SOURCE: Data from NOAA; drawing by S. Kidder.
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FIGURE 3.7 Winds obtained by tracking clouds in successive infrared images. The height of the cloud is determined by the cloud’s temperature. Note that where there are no trackable clouds, no winds can be retrieved. SOURCE: NOAA.
TABLE 3.1 Satellite Data Used to Initialize Numerical Weather Prediction Models in 2006
Satellite Data
HIRS sounder radiances
AMSU-A sounder radiances
AMSU-B sounder radiances
GOES sounder radiances
GOES, Meteosat, GMS winds
GOES precipitation rate
SSM/I precipitation rates
TRMM precipitation rates
SSM/I ocean surface wind speeds
ERS-2 ocean surface wind vectors
QuikScat ocean surface wind vectors
AVHRR SST
AVHRR vegetation fraction
AVHRR surface type
Multisatellite snow cover
Multisatellite sea ice
SBUV/2 ozone profile and total ozone
AIRS
MODIS winds
Altimeter sea-level observations
NOTE: Monthly statistics on the data used in NCEP’s models are available at http://www.nco.ncep.noaa.gov/sib/counts/.
HIRS = High-Resolution Infrared Radiation Sounder; AMSU = Advanced Microwave Sounding Unit; GOES = Geostationary Operational Environmental Satellites; SSM = Special Sensor Microwave; ERS = European Remote Sensing Satellite; AVHRR = Advanced Very High Resolution Radiometer; SST = sea surface temperature; SBUV = Solar Backscattered Ultraviolet.
SOURCE: Lord (2006).
Figure 3.8 shows a time series of one measure of the skill of a representative numerical weather prediction model for 3-, 5-, 7-, and 10-day forecasts. The top line for each set of curves is for the northern hemisphere, where nonsatellite observations are plentiful; the bottom line is for the southern hemisphere, where nonsatellite observations are woefully few. Due largely to our increasing ability to use satellite observations effectively—that is, to assimilate the observations into numerical weather prediction models (e.g., Kalnay 2003)—the difference between northern hemisphere forecasts and southern hemisphere forecasts has steadily decreased, and the overall forecast skill has increased to the point that global 7-day forecasts are now as good as northern hemisphere 5-day forecasts were 25 years ago.
In addition, tests at NCEP show that data from just one satellite instrument, the Advanced Microwave Sounding Unit (AMSU), extend forecast usefulness by 1 day in the southern hemisphere and by about a half day in the data-rich northern hemisphere (Lord 2006). AIRS is also improving forecasting skill (Chahine et al. 2006), and there is evidence that satellite data, particularly QuikScat winds, are improving hurricane track forecasts (Zapotocny et al. 2007). Without question, improvement in numerical weather prediction—on which all forecasts more than a few hours ahead are based—is a major scientific accomplishment of Earth observations from space.
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FIGURE 3.8 Anomaly correlation of 500 hPa height forecasts by the European Centre for Medium Range Forecasting. SOURCE: Updated from Simmons and Hollingsworth (2002). Reprinted with permission from the Royal Meteorological Society, copyright 2002.