Section 9. Forecasting
Objectives: List the tools available for observing dust storms. Describe how mesoscale NWP models can help with a dust storm prediction. List
the dust storm forecasting models and describe their respective advantages. OR: Address key considerations when developing a dust storm
forecast; Outline the steps of a typical dust storm forecast process and know what tools are available for each step; Comprehend how to make a
good dust storm forecast from available data.
Marianne only: Introduction [present their role/task, have them identify dust-related activity that’s possible in this area at this time of year and its
potential impacts], for each time period examine the data and decide about the likelihood of dust storm activity [the products are in a data viewer],
provide general feedback, then discuss what we see in each product. At the end: Case summary, including info about what happened/the impacts
COAMPS forecast plots of surface friction velocity and surface dust visibility for the 24 hour and
12 hour window prior to 12Z February 26.
72h, 48h, and 24h precipitation forecasts valid for 12Z February 26th. February 26 precipitation
forecast plots 72h, 48h, and 24h.ppt
72h, 48h and 24h surface friction velocity, optical depth and surface dust visibility forecast plots
for the February 26th
COAMPS 4 panel plots 72h, 48h, and 24h.ppt
9.1.1 Introduction
Many tools are available to help forecasters predict dust storms, including satellite imagery and
products, surface and upper-air observations, NWP models, and a new generation of
dust/aerosol models.
This section presents a generalized process for forecasting dust storms that was created from
input from operational dust forecasters in the U.S. Department of Defense.
The process is divided into three parts, each defined by the forecast lead time: long range,
medium range, and short range.
We will begin by describing the process and then apply it to a case. By going through it, you
should better understand how the forecasting tools can be used to diagnose dust storm
Although the forecast process refers to DoD models and tools, the process is general enough
for forecasters in other organizations to adapt their data sources and requirements.
9.1.2: General considerations when making a dust storm forecast
Before starting to develop a dust forecast, you should be familiar with your area of responsibility
and local rules of thumb. In particular, you should know:
The locations and types of local dust source regions, for example, if there are lake beds, salt
flats, diapirs, or newly developed drought regions
The types of soil present (heavier particles will settle more quickly)
The impact of local terrain on wind speeds
The wind direction with respect to local dust source regions
How the winds align from the upper levels down to the surface during winter
The process for forecasting dust storms varies depending on the time range: long range (72 to
180 hours), medium range (24 to 72 hours), or short range (0 to 24 hours). Short-range dust
forecasts tend to rely on real-time analyses, while medium- and long-range forecasts are more
model-centric and rely on output from:
Mesoscale models such as the DoD’s COAMPS, DTA-MM5, and DTA-WRF
Global-scale models such as the DoD’s DTA-GFS, NAAPS, and NOGAPS
We’ll examine the three forecast periods on the following pages and then apply the dust forecast
process to the case.
9.1.3: Long-range (72 to 180 hour/3 to 5 day) Dust Storm Forecast Process
The long-range (72 to 180 hr/3 to 5 day) dust storm forecast process has two steps.
Mw: use timeline throughout
Step 1: Look for large-scale, synoptically driven dust events in the 3 to 7.5-day range in global
models such as DTA GFS and NAAPS.
Step 2: Look for model forecast mid-latitude troughs that drive pre- and post-frontal dust storms
in the winter and can amplify the large-scale northerly winds associated with summer shamals.
Such large-scale waves are resolved by global NWP models such as GFS and NOGAPS, while
the associated dust outbreaks are modeled by the global dust models, DTA-GFS and NAAPS.
9.1.4: Medium-Range (24 to 72 hour/1 to 3 day) Dust Storm Forecast Process
For the 24- to 72-hour forecast, you can use mesoscale dust model output from COAMPS, DTAMM5, and/or DTA-WRF, and larger-scale dust forecasts from the global DTA-GFS and/or
NAAPS models. Guidance from the NOGAPS model shows the evolution of larger-scale
atmospheric features and is helpful for identifying conditions favorable for a blowing dust event.
Specifically, here are the steps to follow:
Step 1: Using model output from DTW-WRF, COAMPS, NOGAPS, and/or DTA-GFS, examine
forecast charts for 500-mb height and relative vorticity to identify and track troughs and vorticity
Step 2: Looking at the forecast soundings from either WRF or COAMPS, determine the forecast
stability and wind profile at your forecast time of interest.
Step 3: Check the 6-hr precipitation and MSLP charts to determine where precipitation is
expected, which would decrease the probability of dust lofting.
Step 4: Combine COAMPS forecasts of surface friction velocity, surface winds, and soil
wetness from WRF and/or COAMPS, and your knowledge of the dust source areas to see if
criteria for a potential blowing dust event may be met. (Note that friction velocity is an important
parameter since it incorporates both atmospheric stability and wind speed into one variable.)
Step 5: Examine DTA-WRF and COAMPS forecasts of surface visibility due to dust and dust
concentration, [AFWA: Does a sfc vis forecast specifically say what it’s due to? Are you
correlating sfc vis with dust concentration/optical depth to get a sense of where dust is a factor?
Should we remove “...due to dust and dust concentration” unless it’s clear that the “surface
visibility” shown in the product is due to “dust”. FYI: surface visibility can be lowered due to
hydrometeors. In COAMPS visibility plots ONLY the effects of mineral aerosols are considered,
i.e. dust and not water droplets. To calculate reduced visibilities due to dust alone the equation
requires knowledge of the dust surface concentration at that time step.], WRF/COAMPS
forecasts of winds through the mixed layer, and dust optical depth from WRF/COAMPS [AFWA:
why look at dust optical depth from COAMPS? Doesn’t DTA-WRF provide that? Both models
have dust optical depth. ] [annette’s coment: I have provided the 72h, 48h, and 24h COAMPS
forecasts of surface friction velocity, dust surface concentration, dust optical depth, and
surface dust visibility in a Power Point. These plots can be incorporated to show how with
each model run the dust parameters shift in location or intensity. This is particularly true along
the Iraqi/ Saudi border to Kuwait from the 72h run to the 24h run.]
Step 6: From the model output and your initial analysis, develop a best-guess forecast as to the
onset and duration of any dust events in your AOR in the 24- to 72-hour window.
9.1.5: Short-range (0-24 hr) dust storm forecast process
The process for creating short-range (0- to 24-hour) dust forecasts includes the following steps:
Step 1: Analyze the present state of the atmosphere by looking at satellite imagery (infrared,
visible, and water vapor), upper-air charts, and surface analyses, keeping in mind the location
and characteristics of your dust source regions.
Step 2: Examine the latest sounding from WRF and COAMPS. [pd: Annette says they didn’t
archive them] Note the strength of any inversions (usually during summertime) and determine if
they will break due to turbulent mixing and daytime heating that would ripen the environment for
a dust outbreak.
a. A dry adiabatic lapse rate from the surface through a deep mixed layer will allow the
dust to loft to great heights, especially if winds are from the same direction and increase
with height through the layer. Note the following:
o Dust storms generally occur in this kind of environment
The strongest wind speed aloft within the dry adiabatic layer can be brought to the
The height or top of an elevated dust layer can be approximated by determining
where the lapse rate becomes less than the dry adiabatic lapse rate
b. Dust storms are less likely in a stably stratified boundary layer although narrow plumes
of blowing dust are still possible.
Step 3: To determine the potential duration and type of dust event, pay special attention to dust
lofting in your AOR, local rules-of-thumb about advection, and geographic features such as the
location of dust source regions, terrain, vegetation, and water sources (Why? Is this to imply
dried lake beds, wetlands or wadis once the water has evaporated?). Also note where
precipitation has fallen in the past 48 hours and whether it was convective or stratiform.
Step 4: Use satellite dust enhancement products, such as enhanced IR imagery, RGB imagery,
and other multispectral products tuned for dust detection. (IR enhancements and MSI [spell out
MSI] in conjunction with surface observations to obtain information about the current extent and
location of existing dust plumes and fronts.
Step 5: Make a best-guess forecast as to the onset, duration, and persistence of any dust
events in your AOR in the very short term, using short-range mesoscale model output from
DTA-WRF and/or COAMPS as guidance. The global DTA-GFS and NAAPS models can resolve
large-scale features that drive smaller-scale dust events in the short term but cannot resolve
localized dust features.
9.1.6 The Case Studies
The rest of this section examines a dust storm case from Southwest Asia, focusing on the use of
model data in the dust forecast process. Since these data play a critical role in the long- to shortrange forecast processes, we’ll focus on those periods more than the nowcasting stage when
real-time observational data are more important.
Section 9.2 Case Study
9.2.1 Long-Range Forecast [mw: add time]
Assume that you’re a DoD forecaster assigned to cover
Find map of AOR
the Middle East [AFWA: should we be more specific about
the AOR?]
It’s [add date] February 2010. [AFWA: Is it the 21st? What’s
the time?]
[AFWA: Is there a ‘dust climatology’ product for the region
– would help someone unfamiliar with it?]
Before looking at the data, take a minute to consider the
type(s) of dust activity that is typically found in your area at
this time of year. Select the correct option(s), then click
Dust activity is typically minimal
List other possibilities, mark right choice(s)
Write the feedback! [COMET will do this]
We’ll start by looking at the 120-hr 500-mb forecast charts.
Do you see any indications of upcoming dust storm activity
in the area? As you examine the charts, keep in mind the
process for making long-range dust forecasts.
Which of the following are evident in the charts? Select the
[Is an animation from 0 to 120 hours available? It would be helpful to
correct choices, then click Done. [NOTE for COMET:
see the evolution of the large-scale features.]
Convert this into an interaction where learners view the
charts and decide what they see. Main questions: Is a
duststorm developing and if so, what type is it [postfrontal].
The first indication that a severe dust storm may be on
the horizon is seen in the 500 mb forecast charts five
days prior to February 26th 2010.
The 120-hr NOGAPS 500-mb forecast chart shows an
upper-level trough over the Middle East and Iraq on
February 26.
Considering only the large-scale or synoptic forcing
(not mesoscale features such as the surface low and
associated fronts), DTA-GFS and NAAPS surface
visibility forecasts show a pan regional dust event
impacting north Africa and the Arabian peninsula on
[As with previous products, consider showing visibility product as an
February 26.
animation from 0 to 120 hours if possible]
AFWA: NAAPs shows dust forecast. Is it available as an
animation – would be good to see evolution. See email
sent on 7/9/10.
Medium-Range Forecast (24 to 72 hours): 48 Hours
Marianne only: Arrange the charts per our medium-range
forecast process and make sure we ask the same
questions/have them look for the same things.
AFWA: There was a note about the 300 mb winds not
being mentioned. But it’s not part of the medium-range
fcst process. Would it add much to the discussion –
there’s no mention of how the 300 mb/jet stream winds
analysis impacts the potential for a dust event. Please
provide context – otherwise, we’ll delete sentence.
It’s [AFWA: add the number of days] days later, [add date]
February 2010 [add time] and you’re ready to look at the
48-hr forecasts. Click if you’d like to review the mediumrange dust forecast process first.
Comet: convert rest into interaction
AFWA: Is a 0 to 48 hour animation available?
From the model output and your initial analysis [AFWA: the
one from 120-hrs?], what is your best guess as to the
onset and duration of any dust events in your AOR in the
24- to 72-hour window?
COMET: Write choices and feedback using the following
info. Either have them answer questions about each chart
or review them all and then answer one set of questions.
It’s now forty-eight hours out and the NWP models
continue to forecast a well-developed, mid-latitude trough
over the area.
In the upper troposphere, the forecasted 300-mb winds
show a jet maximum of 150 knots over northern Saudi
Arabia, the northern Arabian Gulf, and western Iran.
The WRF 45-km, 48-hr, 500-mb chart looks very similar
to the NOGAPS 5-day, 500-mb forecast.
The WRF 45-km, 700-mb geopotential height chart
shows that the forecasted trough will extend down the
Red Sea and Saudi Peninsula on February 26th.
AFWA: Is a 0 to 48 hour animation available?
High relative humidities are forecasted for most of Syria,
Jordan and Iraq.
AFWA: Is it more relevant to show forecast precipitation
as mentioned in the medium-range process? Lower RHs
would be more conducive to drying and therefore a dryer
surface with a higher potential for blowing dust event, but
again, forecast precipitation and soil wetness (as
mentioned in the med range process) would seem like
the way to stay more in tune with recommended steps.]
The surface temperature forecast shows the cold front
extending from northern Iraq across the Red Sea and
Sinai Peninsula and into Egypt. [AFWA: This isn’t exactly
in step with the forecast process but is more interesting
from a depiction of synoptic features standpoint.
For Marianne: Draw activity- draw cold front or boundary
of the advancing colder air]
Several features are noteworthy in the COAMPS plot of
forecasted surface friction velocity, streamlines, and
ground wetness. High friction velocities (the shaded
areas) are forecast north and south of the Iraqi border,
Kuwait, over the Saudi Plateau and coastal and inland
areas of the United Arab Emirates, indicating that we can
anticipate dust mobilization in these areas. The
streamline forecast shows southerly flow over the
southeastern portion of the Saudi peninsula and a
surface low in western Iraq.
AFWA: It looks like there are hints of purple contours
(ground wetness) in the plot, but I am really struggling to
see them. I’m not sure how to improve this plot unless
you had a separate layer that showed only the surface
wetness to help distinguish it from the streamlines and
friction velocity shading.] [Annette say: Yes, you are
seeing ground wetness contours shaded in
purple. Unfortunately, this is our default plot.
We do not separate out that variable and plot it
[Note: “surface u*” in the title is aka for “friction velocity”.
AFWA: Shouldn’t we have these products in the case?
Please supply the following if you can:
1) Forecast soundings to help determine stability and
wind profiles (probably not critical if left out), and
2) Forecasts of surface visibility and dust optical
depth[Annette: See Power Point with COAMPS 4 panel
plots of dust parameters.]
I would think it’s more important to show these especially
as one gets closer to the event itself. Also, showing the
visibility and dust optical depth products would make this
period more consistent with the same products shown in
the long-range period.
Short-Range Forecast (0 to 24 hours): 24 hours out
It’s now 25 February 2010 [AFWA: add time] and you are
ready to examine the 24-hr forecasts.
AFWA: We want learners to assess the “state of the
atmosphere” first. Can you provide some standard MSG
imagery (VIS, IR, WV), upper air and surface analyses to
help highlight the major synoptic features? It’d fit well with
the short range process guidelines. Then we’d follow up
with the model output/guidance.] [Annette says: msg
products show dust. To assess the state of the
atmosphere one looks at the viz, IR, and water vapor
satellite imagery. ]
COMET: add text to accompany the analyses...]
Examine the available satellite imagery, upper air charts
(500 mb, and perhaps 700 and 850 mb to help with wind
potential), and surface analyses. Note the positions and
progression of upper level troughs, wind maxima, and
surface features including fronts and pressure gradients.
What are the models forecasting as far as the potential for
a dust storm in your AOR? Check the charts, keeping in
mind the short-range dust forecast process.
COMET: Convert the rest to an interaction]
What is your best guess as to the onset, duration, and
persistence of any dust events in your AOR based on
short-range mesoscale model output?
COMET: Write choices and feedback using the following
info. Either have them answer questions about each chart
or review them all and then answer one set of questions.
matches best to “Step 5” in short range process]
On 25 February (24 hours out), the COAMPS and DTAWRF mesoscale models are predicting a widespread dust
event for East Africa and the Saudi Peninsula. The blue
oval over the Red Sea shows the location of a dust front
forecasted by both dust models.
By comparing the DTA-WRF (bottom) dust surface
concentration with the DTA-WRF visibility (middle) we can
better see the edge of the dust front located over the Red
Sea in the dust surface concentration chart.
COMET: Decide where these forecaster tips should go:
Try to use different dust products from the same dust
model or a different one since each product provides
slightly different information
Looping products is very helpful in identifying
forecasted [need that?] mesoscale dust features and
their movement, extent, and location for any given time
during the forecast period
The blue oval over the southern Arabian Gulf shows the
mobilization of dust from the interior and coastal UAE.
Visibilities of 5 to 0.5 miles (AFWA: surface visibility?) are
forecast for this area and over the waters of the Southern
Arabian Gulf.
The surface friction velocity and 700-mb relative humidity
charts indicate that Jordan, Syria, and most of Iraq will not
experience low visibilities due to dust storms. [AFWA:
These areas won’t have low vis at all or just not from
dust?] Annette comment: Not from mineral dust.
Annette sent gifs for the following
0-24 hour animations for these products?
Surface friction velocity and 700 mb HR charts/model output
Precipitation forecast
[go back to first two “visibility” charts/model output]
Show dust source regions?]
Hydrometeors may reduce visibility.
[should this go after the next paragraph?] The precipitation
forecast (not shown) shows that portions of these
AFWA: Are there any model soundings available to help assess
countries and Iran are likely to experience showers on
airmass stability and depth of mixed layer over the AOR?
February 26. [Annette comment: I have sent AFWA
precipitation plots provided by Kristen George. See
email sent on 7/20/10.]
On the other hand, both COAMPS and DTA-WRF are
forecasting low visibilities north and south of the Iraqi
border and Kuwait as seen in the blue oval over this
region. These models differ with respect to dust activity
over one area: the Saudi Plateau (orange rectangle).
COAMPS is predicting widespread dust mobilization while
DTA-WRF shows little if any dust activity, i.e. good visibility
AFWA: Could dust source regions be shown here, to help
with step 3 of the process? Would be nice to see how
these correlate with the model dust forecast products.
Also are there any “rules of thumb” that might be helpful?
AFWA: As in the medium-range section, I don’t see
mention of model soundings (step 2 in the process). Were
these not relevant, or was there an issue getting the data?
[Annette says: Yes, we do not routinely save the
COAMPS soundings.]
Nowcast (0 to 6 hours) 26 February 2010 valid for 6Z to
AFWA: Can we get some standard MSG imagery (VIS, IR,
WV) and upper air and surface analyses [anneette says:
Kristen sent me upper air analysis. I can send those plots
your way] to help with the state of the atmosphere
assessment? And would fit nicely within the short range
process guidelines. Then follow up with the special RGB
and dust specific products.] [Annette says: Marianne
you should have the msg images Tom Lee sent on
The NRL dust enhancement and MSG satellite products
for 26 February 2010 6 to 12Z show a large-scale dust
event impacting north Africa and the Saudi Peninsula. The
blue ovals on DEP show a dust front over the Red Sea
and dust plumes streaming out of the UAE into the
southern Arabian Gulf.
AFWA: Can we get a higher res version? (Hard to read text label)
[Annette says: The label is imbedded within the image when the
Within the red oval, the clouds exhibit a pinwheel pattern
that qualitatively confirms the high relative humidities and satellite product is made. Marianne, you will have to annotate
each image to create a larger label.]
cyclonic streamline forecasts.
The pink areas indicate that dust is being mobilized and
entrained into the low along the Iraqi/Saudi border as was
forecast by both dust models.
In the DEP and MSG products, elevated dust is more
difficult to identify over Kuwait due to the presence of lowand mid-level clouds. But both DEP and MSG images
confirm the dust activity over the Saudi Plateau as was
forecast by COAMPS.
AFWA: Can we get an animation for this MSG dust RGB product?
[aw says: See comment above.] It would be good to show for this 6
to 12 UTC period for evolution and also help better pinpoint the
source regions, which of course makes Geo satellites so useful for
monitoring events like this.]
Surface observations report dust storms ($) and
suspended dust (S) over eastern Africa, the western and
eastern shores of the Red Sea, southern Iraq, northern
and central Saudi Arabia, and in the United Arab Emirates.
There are no reports of dust storms ($) and suspended
dust (S) over Syria, Jordan, or northern Iraq. Reports of
precipitation (the green symbols) are seen in Syria, Iraq,
and western Iran.
Green symbols:
= continuous rain;
= rain showers,
= slight or moderate thunderstorms.
COMET: To corroborate the observations from a satellite point of
view, if the projections match, have a fade option for toggling
between the MSG dust RGB closest in time and the surface analysis
shown here.
Reported station visibilities on the Metar chart confirm
blinding conditions due to blowing dust:
Along the Iraqi and Saudi border, < 0.25 miles (the
white circle)
Over Kuwait, 0.5 to 1 miles (the red circle)
Over the Saudi plateau, 0.5 to 1 miles (the red
20100226 12Z
COMET: This compilation of columnar observationsreports
[or data?] was
created after the fact by taking each report and color coding the
observations by range.
9.3 Why Dust Model Forecasts Differ
9.3.1 Main Factors Impacting Model Dust Forecasts
As you’ve seen, the process of forecasting dust storms and surface visibility depends largely on model forecasts,
which can differ widely. In this final section of the module, we’ll examine the main factors that account for the
differences between models. These include: how they identify dust sources, their modeled [need that?] dynamics,
and their dust removal processes.
Identifying Dust Sources
How dust sources are identified is the most critical factor in differentiating dust model forecasts. Some models get
their dust source information only from satellites where others use a combination of satellite, topographic and/or
land surface data. For example:
COAMPS gets its dust sources from 10-km, high-resolution MODIS data [ORIG: … from satellite analysis
of high-resolution MODIS data with 10-km precision]
AFWA’s DTA WRF, MM5, and GFS dust models locate dust source regions from satellite data and
ground topography, which can vary in precision from 15 to 55 km
NAAPS uses a combination of satellite data and land surface information to identify dust sources on a 1degree scale [what’s that mean?]
The important thing is how a model determines the number and extent of dust sources in each grid box. If a
model ‘thinks’ that many dust sources cover much of a grid box, it may forecast [right word?] large, broad plumes
for the area. Another model may not show any dust sources for that same box. If this depiction is wrong, it may
reflect a weakness in how the model determines erodible or dust-producing areas.
The models used in the 26 February case had [or have?] varied dust source functions: some forecast broad
plumes, others narrow plumes. Some had too many dust sources, others too few.
For example, COAMPS forecasted several refined plumes for the interior of the UAE and its coast (show Figure
12, DEP image), while DTA-WRF forecasted a broad dust plume with low visibilities (1 to 0.5 miles) from Qatar to
the Strait of Hormuz. The COAMPS forecast was based on a few, limited dust sources, whereas DTA-WRF was
based on too many.
Over the Saudi Plateau, COAMPS over-predicted surface dust concentrations, leading to a broad area with
visibilities from 2 to 0.5 miles. In contrast, DTA-WRF did not forecast any reduced visibility plumes. This suggests
that COAMPS had too many dust sources for this area, while DTA-WRF had too few.
Modeled dynamics
NWP models produce different dynamical forecasts due to their sensitivity to initial conditions. This can lead to
different atmospheric motions and stability. As a result, the strength and location of upper-level short waves,
surface lows, associated fronts, and surface winds will vary. Differences in the forecasted strength and location of
surface winds account for different dust visibility forecasts among models.
Dust removal processes
Finally, a model’s handling of soil moisture and precipitation impacts its treatment of dust production and dust
removal. Source areas with significant rainfall in previous time steps will have high soil moisture values and
suppress dust production in current forecasts. Since rain removes suspended dust particles, differences in
forecasted precipitation patterns lead to different visibility forecasts.