Satellite Surveillance of Desert Dust Storms

S.D. Miller
Marine Meteorology Division

he consensus of numerous Navy Meteorology/Oceanography (METOC) post-deployment reports from Operation Enduring Freedom (OEF) holds desert dust accountable for most common and significant adverse impacts to operations. Specifically, these storms impaired visibility, obscured targets, and rendered laser-guided weaponry ineffective. Satellite-based detection of dust is a difficult problem, due in part to observing-system limitations. An unprecedented interagency coordination in support of the War on Terror mitigated this problem by making available a global, near real-time dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS). NRL designed a novel technique for enhancing dust over water and land, leveraging previous capabilities with these new high spectral/spatial resolution MODIS data.

INTRODUCTION

One does not have to dig deeply into the growing compilation of Operation Enduring Freedom (OEF) post-deployment Navy Meteorology/Oceanography (METOC) reports to find strong arguments for the need to better predict and observe dust storms. The following testimony from a METOC Officer supporting aircraft carrier operations in the Northern Arabian Sea (NAS) embodies this theme:

Such difficult environmental conditions cause any number of undesirable mission outcomes, ranging from diverts/aborts to catastrophic mishaps with potential loss of life.

Long before the OEF-critical demand for improved METOC dust support arose, the general need was well established. Major Naval aviation accident statistics over a nine-year period (1990-1998)¹ find that slightly more than half (54%) of these were associated with visibility problems, representing annual losses of ~$50 million per year. Moreover, over half (56%) of those visibility-related mishaps were considered avoidable, provided sufficient forecasting and observational tools. Not included in the study are the potential losses during times of conflict from wasted equipment operations costs, jettisoned ordnance, and off-target laser-guided weaponry due to visibility-impaired conditions at or near the target.

Satellite-based dust detection over the desert terrains characterizing much of the OEF domain requires an observing system capable of extracting as much dust-specific information from the scene as possible. The current approach improves previous methods in this regard through the use of high spatial and spectral information available from the Moderate Resolution Imaging Spectroradiometer (MODIS), a state-of-the-art instrument flown aboard NASA's recently launched Earth Observing System (EOS) Terra and Aqua satellites. This paper begins with an overview of why dust detection is possible, followed by a brief description of MODIS and the algorithm designed to exploit the advantages of this sensor. Presented next are several examples illustrating dust storm enhancement capabilities, with additional applications to smoke and volcanic plume detection. The paper closes with a summary of ongoing efforts to provide this new resource to the warfighter during OEF and beyond.

PHYSICAL BASIS FOR DETECTION

The fundamental principles of dust detection are spatially, spectrally, and temporally based. The idiosyncrasies of dust within these paradigms are what allow for its decoupling from other components of the complex scene. We discuss some of these elements here, placed in the context of previous research done in this area.

Spatial Information

Moderate levels of dust over land cause visual blurring of otherwise sharply definable surface features. This so-called "adjacency effect" has proven useful in detecting dust,² although the method faces inherent challenges over laminar desert backgrounds where the propensity for contrast reduction is reduced. At visible (VIS) wavelengths, highly reflective dust contrasts against darker backgrounds such as vegetation or bodies of water. At infrared (IR) wavelengths, depressed brightness temperatures from elevated (and cooler) dust over hot surfaces yield similar contrast information. Reference 3 demonstrates enhancements based on these VIS/IR spatial contrast principles. Because the corresponding signatures of clouds are similar to dust, an implicit requirement for distinction is recognition of differences between the cloud and dust spatial structures. This inspection is not always straightforward, particularly in the case of thin cirrus clouds that spatially appear very similar to dust.

Spectral Information

An important spectral property allowing for dust detection in the IR is the "split-window" difference (e.g., Ref. 4). The signature arises from the higher spectral absorption of dust sensed at 11.0 micrometers (mm) compared to measurements at 12.0 mm. This spectral behavior contrasts liquid and ice clouds where the opposite absorptive properties hold. The split-window signature is less pronounced for thick dust very close to the surface, where transmission effects are smaller. Additionally, some land surfaces produce ambiguous signatures in the absence of dust.

Mineral dust becomes increasingly absorptive with decreasing VIS wavelength (i.e., progressing from red toward blue light), corresponding to a monotonic increase in the complex part of the imaginary index of refraction (n_i).⁵ These properties result in dust coloration, as illustrated conceptually in Fig. 1. Dust appears as shades of yellow/orange due to its preferential absorption of blue light, whereas clouds (having small and relatively invariant n_i across the VIS) yield shades of gray to white depending on the strength of illumination. The reasoning behind why the color yellow is the outcome of preferential blue light absorption is explained in the context of red/green/blue composites further along. Exploiting the dust coloration properties for the purpose of enhancement requires a radiometer with spectral resolution sufficient to partition the VIS spectrum into the required components.

These principles have been applied⁶ to the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), which features eight narrowband channels across the VIS spectrum. The technique uses a "normalized dust difference index" (NDDI) between the red (670 nanometer (nm)) and blue (443 nm) channels of SeaWiFS, defined such that dust produces large positive differences while clouds produce relatively smaller differences. Normalization ensures enhancement of weak dust signals over dark backgrounds. The method's fundamental shortcoming is that land areas are also enhanced since their spectral properties at VIS wavelengths are similar to those of dust. Hence, it is a method limited almost exclusively to overwater applications.

Temporal Information

The ability to observe and track feature motion by looping consecutive satellite images is very useful for dust detection. For this reason, many applications consider only geostationary satellite imagery (typically having 30-minute refresh). Unfortunately, given current instrumentation limitations on the geostationary platform, the trade-off for this high temporal resolution is reduced spatial and spectral information. The featured work concentrates on the superior dust detection capabilities of low-Earth-orbit (LEO) high spatial/spectral resolution sensors, with multiple overpasses from various LEO satellites serving as a possible temporal surrogate.

THE MODIS OBSERVING SYSTEM

Instrument Description

MODIS instruments operating aboard the EOS Terra (1030 local equatorial crossing time; descending node) and Aqua (1330; ascending node) satellites offer a 2,330-km cross-track swath with 36 narrowband channels situated between 0.4 and 14.4 mm. All IR channels are available at 1-km subsatellite resolution, and a subset of VIS and near-IR channels exist at 500-m (channels 3-7) or 250-m resolutions (channels 1 and 2). Many of these channels open the door to innovative or entirely new atmospheric sensing applications, including improvements for dust detection.

Data Source and Timeliness

MODIS was never intended to function as an operational instrument — the War on Terrorism scripted this role. The National Oceanographic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) answered the Department of Defense's (DOD) call for assistance by making the global EOS Terra and Aqua data available in near real-time. Data arrive typically 1.5 to 3.5 hours after collection — timeliness sufficient for including value-added products within the METOC operational decision loops. The proof-of-concept demonstrated by this arrangement played a critical role not only in the immediate benefit to OEF, but also in the lobbying for procurement of sorely needed X-band direct broadcast receiving stations at the Navy Regional Centers in both Rota (Spain) and Bahrain.

THE NEW ENHANCEMENT

The new NRL dust enhancement combines elements of previous methods with the spatial/spectral advantages of MODIS to form a novel, unified product. Because of the very different restrictions between water and land backgrounds, two distinct algorithms operate on their respective backgrounds as determined by a land/sea database. Careful scaling minimizes discontinuities of enhanced dust crossing coastal (algorithmic) zones.

Understanding Color Composites

A prerequisite for understanding the appearance of the dust enhancement is a familiarity with the three-color composite technique. The concept is as follows: three primary colors (red, green, and blue) form the axes of a "color cube." In the example of an 8-bit computer display, brightness magnitudes for each primary color range from 0 (black) to 255 (full red, green, or blue saturation). This forms a cube of dimension 256 x 256 x 256 elements whose indices map to a discrete representation of all possible colors, based on varying combinations of the primary color brightness values.

Figure 2 depicts the appearance of the outer surfaces of such a cube, showing how the primaries combine and transition across the three-dimensional color space. This provides a suitable framework for visualizing how the various components of VIS light combine to form all the colors we see. White light is the combination of full red/green/blue saturation, while yellow tonalities arise from high values of green and red with low amounts of blue. Extending this to the real-world example of dust illuminated by a source of white light (the Sun), the removal of blue light (via dust absorption) results in the preferential scattering of yellow light - explaining the observed color of dust.

Creation of a "true color" composite from satellite imagery requires sufficient spectral resolution to separate the red, green, and blue components of VIS light. After applying atmospheric corrections and appropriate scaling, these channels become the respective red, green, and blue indices (sometimes called "color guns") of the color cube described in Fig. 2. The result is an image with an appearance similar to what we would observe with our own eyes. For the dust enhancement, a multispectral channel combination designed to enhance dust replaces the red gun of the true color product. The effect is for dust to possess relatively brighter red tonality throughout the enhanced imagery. The nondust components appear as red-depleted (e.g., cyan clouds, green land) and generally darker tones to focus attention toward the dust features of interest.

Channel Selection

The current algorithm uses 7 of the 36 available MODIS channels to exploit the spatial and spectral contrast features of dust. Listed in terms of [channel index; central wavelength; native spatial resolution; description] and in order of increasing wavelength, they are as follows: (3; 469 nm; 500 m; blue), (4; 555 nm; 500 m; green), (1; 645 nm; 250 m; red), (2; 853 nm; 250 m; reflective IR), (26; 1.38 µm; 1 km; short-wave water vapor), (31; 11.0 µm; 1 km; IR clean window), and (32, 12.0 µm; 1 km; IR dirty window). The over-water algorithm uses MODIS channels 2, 3, and 4, and the overland algorithm enlists all seven channels listed abov.

Overwater Component

The relative ease of dust detection over water (aside from conditions of shallow water or heavy alluvial/biological material suspension) using VIS spatial/spectral contrasts allows for use of a more aggressive method geared toward enhancing fine details of tenuous dust features. Accordingly, the overwater algorithm adopts the NDDI technique described previously.⁶ An important part of this processing is the molecular scatter correction applied to the VIS channels, based on radiative transfer simulations computed offline and stored in look-up tables. The correction reduces limb-brightening effects that would otherwise wash out the imagery on the swath edges.

Overland Component

Detection of dust over bright land backgrounds such as deserts is far more difficult than over water, and requires additional IR information to separate the dust signal from the other components of the scene. The premise for the overland enhancement is threefold: (i) elevated dust, having cooled to its environmental temperature, produces depressed IR brightness temperatures against the hot skin temperature of the land background; (ii) this cool layer of dust is distinguishable from a cloud with the same radiometric temperature using the NDDI technique; and (iii) split-window differencing reveals dust. In the three-color composite dust enhancement, the blue and green color guns contain information from the corresponding blue/green channels of MODIS, and the red gun contains a weighted combination of items (i) to (iii). Statistical composites from many dust storm cases provided the optimal scaling and weighting coefficients. The short-wave water vapor channel (1.38 μm) provides filtering of cirrus clouds whose cold IR temperatures sometimes cause ambiguity.

LIMITATIONS OF ALGORITHM

The daytime-only MODIS dust enhancement is not without its own assortment of interpretive caveats. The overwater component has the undesirable effect of enhancing the region of Sun glint (near-specular reflection of the solar disk off water surfaces) as dust. The current product flags a glint zone based on a prescribed minimum glint angle. High concentrations of sediments suspended in water (e.g., associated with river runoff) occasionally also give rise to false dust enhancements.

Over land, cold surfaces may appear falsely enhanced due to the similar VIS/IR properties of thick dust. The overland algorithm includes a terrain elevation database to filter out a subset of these effects. Depending on surface temperature, an optically thick layer of dust (producing small split-window differences and IR contrast signatures) near the ground may go undetected, a characteristic observed most commonly near strong point-sources of dust. The scaling thresholds and weighting coefficients of the IR enhancement components require seasonal tuning, mainly to reduce false enhancements emerging during the cold winter months.

Because of increased optical paths at higher sensor zenith angles, dust on the edge of the satellite swath exhibits a stronger (brighter) enhancement than the same dust observed near satellite nadir. While brighter pink tonalities do correspond to higher dust opacity over local regions (e.g., of several hundred km), the current product does not quantify this opacity in terms of optical depth, particle size, slant range visibility, or laser attenuation. It is a qualitative dust identifier and a first logical step toward physical retrievals on the subset of pixels thought to be dust. With these limitations in mind, we proceed to highlight the strengths of the enhancement through a series of examples.

DUST ENHANCEMENT EXAMPLES

EgyptAir Accident

On May 7, 2002, an EgyptAir passenger aircraft crashed into a hillside during an emergency landing attempt near Tunis, Tunisia, killing 18 of the 60 people onboard. Local weather at the time of the accident included fog, rain, and blowing sand from the Saharan Desert interior. NRL dust products supported the National Transportation Safety Board during its investigation of this accident.

Near the time of the crash, Terra MODIS collected the imagery shown in Fig. 3. The true color product (left panel) shows the city of Tunis obscured by a squall line. A veil of dust fans into the Mediterannean Sea, carried northward by strong southerly winds associated with the advancing storm system. Subtle adjacency effects indicate additional inland dust westward of the squall line. The corresponding enhancement (right panel) reveals considerable inland dust throughout the cloud-free regions of the storm. Dust areas appear as shades of pink, clouds are cyan, and land areas free of overlying dust are green. Since the enhancement cannot detect dust obscured by cloud (although dust-over-cloud generally is detectable), only the inference of its presence near the Tunis crash site was possible, based on its observance on either side of the squall line.

False Dust Fronts

Among the many caveats to dust imagery analysis are sudden transitions in vegetation regimes that sometimes masquerade as false dust fronts. The Indus River valley of Pakistan features many such "desert-meets-oasis" discontinuities. The true color image of Fig. 4 notes two possible dust fronts in advance of a storm system crossing central Pakistan. The dust enhancement reveals that front A (yellow dotted line) is in fact a vegetation boundary, while front B (red dotted line) is a true dust front. Also evident in the enhancement are additional fronts not obvious in the true color imagery.

FIGURE 3
Tunisian dust storm captured by MODIS, thought to be a visibility-reducing factor in the crash of a Boeing 737 commercial aircraft.

FIGURE 4
Dust in advance of a baroclinic system over central Pakistan, highlighting the enhancement's ability to distinguish between surface features and actual dust fronts.

Thin Dust Over Bright Land

Figure 5 highlights another OEF-domain application of the dust product. Strong northerly winds in the wake of a passing storm system carry dust from the deserts and dry lakebeds of eastern Iran, southern Afghanistan, and Pakistan. Winds channeled through coastal valleys spawn numerous dense dust plumes, clearly visible in the imagery as they stream into the NAS. The corresponding dust enhancement shows several additional plumes over land, previously washed out by the bright topography. The solid, sharply defined pink object near the inland plumes is a dry lakebed, enhanced for reasons explained later.

ADDITIONAL APPLICATIONS

Analysis of Dust Source Regions

Knowledge of the likely source regions for dust under certain environmental forcing conditions is critical to improving dust-forecasting models. Strong northerly winds channeled into the Margow Desert basin of southwestern Afghanistan produce the recurring dust pattern observed in Fig. 6. Several plumes originate from dry lakebeds noted in the imagery. With high concentrations of fine (and easily lifted) silt deposits, these areas often serve as point sources for dust. The lakebeds are enhanced in the dust product by applying the overwater (NDDI) algorithm to the dry land pixels.

Volcanic Ash Plume Detection

Volcanic aerosol poses an underemphasized and poorly understood hazard to turbine engine-powered aircraft. The danger lies in the very small glass-like particles constituting volcanic ash, which melt readily as they come into contact with certain parts of the hot engine interior. Subsequently they resolidify, clogging air intakes and damaging turbine blades to the point of engine failure. Commercial airline pilot accounts from near-tragic encounters with volcanic ash (steep-dive recoveries from complete engine stalls) noted difficulties in visually discerning the ash haze from the benign cirrus clouds commonly encountered at those same flight levels.

The same physics that allow mineral dust detection in the current product applies to some varieties of volcanic ash plumes. The recent eruptions of Mt. Etna, on the island of Sicily, provided a glimpse into these capabilities. Figure 7 illustrates the detailed structure of Etna's plume as upper-level winds carry it southward across the Mediterranean Sea. The level of detail, combined with the high sensitivity of the NDDI to low concentrations, suggests some utility for the dust enhancement in this regard.

Oil Fire Detection

During the Gulf War, Iraqi troops set fire to numerous oil wells in Kuwait. Pitch-black smoke issuing from these fires cloaked the Arabian Gulf skies, impacting Naval flight operations. The difficulty in satellite monitoring of such plumes over dark (low VIS contrast) water backgrounds warrants examination of the dust enhancement's utility in this capacity. An opportune MODIS overpass captured a small and short-lived plume emerging from an oil fire in southern Kuwait. Pending a detailed analysis, the preliminary results shown in Figure 8 indicate that properties of these plumes are conducive to their enhancement over both land and water under the existing method.

SERVING THE WARFIGHTER

The MODIS dust products are of little use to operations without the proper delivery vehicle in place. In a parallel effort, NRL developed the "Satellite Focus" web page (see "A 'Satellite Focus' for the War on Terrorism," p. 103), designed specifically for hosting satellite imagery in a new and comprehensive way. Cooperation with Fleet Numerical Meteorology and Oceanography Center (FNMOC) made possible the rapid transition of these new products via Secure Internet — the network used by bandwidth-limited Navy assets worldwide. Fully automated imagery processing software linked with this dynamic web interface achieves rapid turnaround (on the order of minutes) of near real-time satellite products. Positive and constructive feedback received from a growing base of DOD and coalition users propels the ongoing development of this new resource and refinement of satellite products to better suit warfighter needs.

SUMMARY AND CONCLUSIONS

A satellite technique for identifying dust over water and land using improved spatial and spectral resolution data from MODIS has been designed. The dust enhancement is one of many new and innovative satellite products supporting forecast and strike briefs during OEF. Future refinements include dynamic treatment of the sun glint zone based on surface wind field analysis, overlay of frictional surface wind fields, and creation of a quantitative dust mask. Additional IR channels from MODIS are being explored in the development of a companion nighttime dust enhancement.

Among the many lessons learned in the wake of September 11, perhaps the one bearing most relevance to the DOD research community is the need for a more proactive and forward-focused mindset in terms of both product design and accelerated transition. We must ensure that research topics are based on "need driving technology" principles, and that the fruits of our efforts extend beyond the annals of literature to reach and truly impact the end users situated at the "pointy end of the spear." NRL embraces this new philosophy, and continues to push the envelope of satellite remote sensing technology to benefit those who willingly put themselves in harm's way to protect our freedom.

ACKNOWLEDGMENTS

The ongoing efforts of NOAA/NASA colleagues (Jim O'Neal, Joy Henegar, Paul Haggerty, et al.) in support of near real-time MODIS data are gratefully acknowledged.

[Sponsored by ONR and SPAWAR]

References

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³W.E. Shenk and R.J. Curran, "The Detection of Dust Storms Over Land and Water with Satellite Visible and Infrared Measurements," Mon. Weather Rev. 102, 830-837 (1974).
⁴S.A. Ackerman, "Remote Sensing Aerosols Using Satellite Infrared Observations," J. Geophys. Res. 102, 17,069-17,079 (1997).
⁵E.M. Patterson, D.A. Gillette, and B.H. Stockton, "Complex Index of Refraction Between 300 and 700 nm for Saharan Aerosols,"
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⁶S.D. Miller, "SeaWiFS True Color, Vegetation, and Dust Enhance-ment Processing at NRL Monterey," NRL FR/7540/02-0002,
March 2002.