Upon completing this section, you should be able to interpret 85-91-GHz imagery and 36-37-GHz imagery, as well as discuss their primary uses and how these types of images are derived. Furthermore, you should be able to discuss the primary uses of the precipitation radar and microwave imager instruments aboard the TRMM and GPM satellites. Finally, you should be able to discern whether a particular product discussed on the page comes from an active or passive remote sensor.
Our studies of remote sensing from satellites so far have mostly focused on techniques and products that are based on conventional satellite imagery. Even multi-spectral images are merely created by using various wavelengths used to create visible and infrared images. Now, however, we're going to transition into some more sophisticated applications of remote sensing from satellites. In this section, I'm going to focus on satellite-based detection of precipitation structures and rates. Satellites play a crucial role in this area because tropical cyclones spend so much time outside of the range of land-based radar networks. First, we'll investigate imagery created from satellite detection of microwave radiation between 85 GHz and 91 GHz.
One of the characteristics that you've learned about a tropical cyclone's eye is that it is generally rain free, but it is not often completely cloud free. Either some low clouds exist in the eye and/or high clouds obscure the presence of the eye altogether on conventional satellite imagery. For example, check out the enhanced infrared satellite image at 15Z on September 1, 2009 (below), which shows Hurricane Jimena near the southern tip of Baja California. At the time, Jimena had maximum sustained wind speeds of 130 knots, and a central pressure of 933 mb. Given these data, you might suspect that Jimena would display a well-defined eye on conventional satellite imagery. But, alas, high clouds almost completely obscured Jimena's eye, and it would be tough to get a fix on the storm's center under these circumstances.
Even though enhanced IR imagery didn't provide a good look at Jimena's core structure, thanks to passive microwave imagery utilizing single frequencies between 85 GHz and 91 GHz, forecasters could still see that Jimena had an eye. Such imagery comes from passive microwave sensors like the Special Sensor Microwave Imager (SSMI), the Special Sensor Microwave Imager / Sounder (SSMI/S), and the Advanced Microwave Scanning Radiometer (AMSR). These instruments are mounted aboard the polar-orbiting satellites you may have encountered in the previous section. Feel free to explore these links if you're interested in learning more about these sensors.
The image below shows data collected by the SSMI/S mounted aboard the U.S. Air Force Defense Satellite, F-16. This particular image was created using 91-GHz microwave radiation, and note that Jimena's eye now shows up much more clearly than on the enhanced IR image above. Detecting the high-level structure of the core of tropical cyclones is a primary use of 85-91-GHz imagery because at the wavelengths used to create these images, we can "see" right through high-altitude cirrus clouds into the eye.
So, how should we interpret this image? Why is Jimena's eye evident on this image, but not the enhanced infrared image? After all, both images are plotting the same variable, called "brightness temperature," which is the temperature of a hypothetical object that absorbs all radiation that strikes it (brightness temperature is also sometimes referred to as "equivalent blackbody temperature"). But, because the two images are utilizing different wavelengths (frequencies) of radiation, they're showing us different things. The 91-GHz image doesn't really show us high, cold cloud tops like conventional infrared imagery does.
Focusing on the spiraling pattern of low brightness temperatures associated with Hurricane Jimena (red, green and yellow), it stands to reason that not much 91-GHz radiation was reaching the satellite at this time. To better understand why, check out the schematic below which outlines the plight of 91-GHz radiation emitted upward from the ocean, raindrops, and cloud droplets. To summarize, 91-GHz radiation weakly upwelling from the ocean surface gets mostly absorbed or scattered away by raindrops and cloud droplets below the freezing level in a tall thunderstorm (assume that the storm developed in the eye wall or spiral rain band of a hurricane). Raindrops and cloud droplets also emit some 91-GHz radiation upward. This upwelling 91-GHz radiation from the top of the "rain layer" is primarily what reaches the satellite, but not before it gets scattered and absorbed above the freezing level by precipitation-sized ice particles like hail and graupel. Higher up in the storm, tiny ice crystals in cirrus clouds are virtually transparent to 91-GHz radiation (it's transmitted through the tiny ice crystals), but the damage has already been done. Without reservation, the 91-GHZ signal reaching the satellite in a tall thunderstorm is very weak indeed.
The weak 91-GHz radiation reaching the satellite correlates to very low brightness temperatures. So, when we see very low brightness temperatures on 85-91-GHz imagery, we're really seeing the signature of deep convection (characterized by the areas where the signal from 91-GHz radiation has been weakened the most by large ice particles like hail and graupel). For practical purposes, this trait of 85-91 GHz imagery:
- allows forecasters to see the eye of a hurricane that's shrouded by high clouds
- allows forecasters to assess the structure of hurricanes over remote seas by revealing the patterns of deep, moist convection in the storm's eye wall and outer rain bands
For the record, a few "twists" on 85-91-GHz images actually exist. Scientists have made some tweaks to the basic product in order to make it more useful. If you're interested in reading about these "twists," check out the upcoming Explore Further page.
One of the major limitations of 85-91-GHz imagery is that one of the several satellites equipped with a microwave sensor passes over a tropical cyclone, on average, every four to five hours (time lags can be as brief as 30 minutes or as protracted as 25 hours). So, there can be long gaps between data for any tropical cyclone. Researchers at the University of Wisconsin devised a creative technique to fill in the time gaps with morphed 85-91-GHz images. The product is called MIMIC (Morphed Integrated Microwave Imagery at CIMSS) and it can be very helpful for assessing changes to the structure of a tropical cyclone's core structure (and thus, its intensity). For example, check out this MIMIC loop of Hurricane Ike as it made landfall on the upper Texas Coast on September 13, 2008. The loop really shows the breakdown of Ike's eye wall (the partial ring of yellows and oranges) after landfall. Pretty cool, eh? If you really enjoy following tropical cyclones in real-time, I highly recommend keeping an eye on the recent MIMIC loops posted on the CIMSS site.
While 85-91-GHz imagery is useful for identifying areas of deep convection within a tropical cyclone, it's not particularly useful at looking at the low-altitude structure of a storm because of the impacts that the large ice particles above the freezing level have on upwelling 85-91-GHz radiation. To get a better view of the low-level structure of a tropical cyclone, forecasters turn to imagery based on 36-37-GHz radiation, which works much like 85-91-GHz imagery, with one key difference. The 36-37-GHz radiation that upwells from the top of the "rain layer" is not scattered and absorbed by large ice particles or tiny ice crystals above the freezing level (here's a visual schematic outlining the process).
As a result, brightness temperatures are higher because the passive microwave sensor aboard the satellite detects a relatively large portion of the upwelling 36-37-GHz radiation from its source -- raindrops below the freezing level. And, because the majority of the radiation from lower altitudes reaches the satellite, 36-37-GHz imagery gives forecasters a better sense of the overall low-level structure of tropical cyclones. For example, we can see the signature of the small eye of Hurricane Wilma from this 36-GHz image from 1845Z on October 20, 2005. This utility of 36-37-GHz imagery also makes it a better choice than 85-91-GHz imagery for pinpointing a tropical cyclone's center. For a more in-depth explanation of this advantage of 36-37-GHz imagery, check out upcoming Explore Further page.
Before moving on, however, I want to point out that forecasters can use 36-37-GHz imagery in tandem with 85-91-GHz imagery to assess the vertical structure of tropical cyclones. Since 36-37-GHz imagery gives a better look at the low-level structure, and 85-91-GHz imagery gives a better look at the high-level structure, forecasters can compare the locations of the low-altitude center and high-altitude center to see if the center of the storm tilts with increasing height. If the center notably tilts with height, that's often a sign that the storm isn't healthy and may be hindered by strong vertical wind shear.
Quantitative Precipitation Estimates
While 85-91-GHz and 36-37-GHz imagery do a good job of showing us the overall precipitation structure of a tropical cyclone (by highlighting deep convection and the details of the low-level rain layer, respectively), they don't quantitatively indicate rainfall rates. Remote sensing from satellites can help with that, too, as the rainfall estimates in the image below (in millimeters) suggest. The data in the image were collected from the Tropical Rainfall Measuring Mission (TRMM) satellite as Hurricane Dolly approached the southern Texas coast from July 20 - 25, 2008.
TRMM was launched in 1997 through a partnership between NASA and the Japan Aerospace Exploration Agency, and its launch revolutionized precipitation detection from satellites. Given that "tropical" is part of its name, the satellite's focus on low latitudes should be no surprise. TRMM's orbit ranged from 35 degrees North to 35 degrees South (basically covering the tropics and subtropics) as illustrated by this artist's rendition of TRMM's orbital path.
TRMM contained five instruments, but the last of them became inoperable in April, 2015. I'll still briely describe TRMM's two instruments for measuring rain rate since they're basically the prototypes for instruments aboard other satellite missions: TRMM's active remote sensor--Precipitation Radar (PR), and TRMM's passive microwave sensor--TMI (TRMM Microwave Imager). I'll only provide a quick summary, but you're welcome to read more about their capabilities and limitations if you would like (PR overview; TMI overview).
TRMM PR was the first space-borne instrument designed to provide the three-dimensional structure of storms. PR transmitted pulses of microwave radiation and waited for return signals, much like a ground-based radar. TRMM PR's main uses were depicting vertical rain structure, surface rain-rate, and it could discriminate between convective and stratiform rain.
Meanwhile the TMI carefully measured weak microwave energy naturally emitted by the Earth and the atmosphere and used it to infer rainfall rates. What makes the TMI different from 85-91-GHz imagery and 36-37-GHz imagery (which do not quantitatively estimate precipitation)? TMI's use of multiple frequencies (10.7, 19.4, 21.3, 37, and 85.5 GHz) allowed for the quantitative estimation of rainfall rates. Imagery generated using a single frequency between 85-91-GHz or 36-37-GHz can't display precipitation rates. While TMI had a broader scanning swath than PR, it also collected data at a lower resolution, so the bottom line here is that TMI provided an estimate of surface rain across a broad swath, and coarse information on the vertical structure of rain. PR, meanwhile, provided a narrower footprint but higher 3-D resolution. To see the trade-off between the data collected by these two instruments, check out the annotated image below.
The image above is the PR / TMI image of Hurricane Wilma at 1740Z on October 19, 2005. Rain rates are expressed in inches per hour. Note that the PR / TMI data were superimposed on the 1615Z visible satellite data from GOES-12. The wider swath, bounded by the two thicker yellow lines, corresponds to the data collected by TMI. The narrower swath, bounded by the two thinner yellow lines corresponds to PR data. Note that the PR data, which cuts through the rain bands north of Wilma's core, is much more detailed compared to the TMI data. But, the PR scan completely missed Wilma's core. On the other hand, the TMI data is less detailed, but has wider coverage.
More recently, another precipitation-measuring satellite mission, the Global Precipitation Measurement (GPM) was launched in 2014 to expand upon TRMM's substantial legacy. One main difference between the two missions is that GPM has nearly global coverage, as its name implies, so it provides data at higher latitudes than TRMM. Like TRMM, GPM includes a precipitation radar (active sensor) and a passive microwave imager.
The GPM's precipitation radar is the first satellite-based dual-frequency precipitation radar (its acronym is "DPR" for this reason--the "D" stands for "dual"). The dual-frequency nature of DPR makes it more sensitive to areas of light precipitation and snow compared to TRMM PR. Meanwhile, the GPM Microwave Imager (GMI) works much like TMI, except that it utilizes more channels and has a higher resolution. As with the instruments on TRMM, DPR's scanning swath is narrower than GMI's (although both are slightly larger than their TRMM predecessors). If you're interested in learning more details about these key instruments aboard the GPM satellite, feel free to read more (DPR overview; GMI overview).
Now that you're familiar with satellite-based qualitative and quantitative looks at precipitation within tropical cyclones, you might be wondering, "where can I access all of this data?" For more on data resources and some of the products available, check out the Explore Further page that follows. Otherwise, we'll stick with the theme of remote sensing using microwaves and explore a special microwave sounder (a sounder provides a vertical profile of a meteorological variable) used in tropical forecasting.