A look at the 16 Jan 2014 dust storm in eastern Colorado using VIIRS imagery

Strong winds coupled with dry soil led to widespread blowing dust across the eastern plains of Colorado and areas east on Thursday 16 January 2014.  A short video clip shows the blowing dust obscuring visibilities in Logan County in far northeastern Colorado (see www.youtube.com/watch?v=uxMdMTzlRFI ).  The lowered visibilities in the blowing dust resulted in a multi-car accident that closed Interstate 70 near Burlington Colorado (close to the Kansas border) for several hours from 11:30 AM MST to 4:25 PM (1830 to 2325 UTC).  A story of the dust storm and the accidents that closed Interstate 70,  courtesy of Denver 7 News, can be found here http://www.thedenverchannel.com/news/local-news/dust-storm-closes-eb-i-70-us-24-to-kansas-line-us-34-closed-as-poor-visibilty-causes-accidents.

Below is a surface plot from early afternoon on the 16th showing sustained wind speeds of 30 to 40 knots with gusts as high as 55 knots.

Surface plot at 2043 UTC on 16 January.

In this blog entry we will take a look at how the dust appeared in standard GOES visible imagery and compare this to different imagery from the SUOMI NPP VIIRS instrument Polar satellite.  Some of the images we will show demonstrate the capabilities that will be available when GOES-R is launched.

We start with a look at “standard” GOES visible imagery during the event, shown for two times below.  In the visible images the plains of eastern Colorado and surrounding areas have a collection of clouds at different levels in addition to some areas of old snow cover as well as the blowing dust.  From this imagery alone it is difficult to distinguish between these.

Shown below is similar type of visible satellite imagery but using VIIRS with a natural color background and of course higher spatial resolution (~0.5 km vs 1.o km from the current GOES).  Right away we can see that the improved contrast and resolution allows one to see dust plumes in the first image below from 1848 UTC, but things are not so apparent in the second image from 2029 UTC.

VIIRS True Color visible satellite image at 1848 UTC on 16 January.

VIIRS True Color visible image at 2029 UTC on 16 January.

Using different bands from VIIRS a specialized type of imagery can be created which isolates the dust, making it stand out far more clearly.  CIRA creates two types of dust discrimination imagery, one with the dust highlighted in yellow and the other where the dust has a pinkish color, as shown below.  The purpose of these products is to clearly isolate dust from other surrounding clouds and general background.

Pink dust product using NPP VIIRS imagery at 1848 UTC on 16 January

Pink dust product using NPP VIIRS imagery at 2029 UTC on 16 January

The above imagery is especially useful for the 2029 UTC time, when the earlier visible satellite image showed a more complex mix of dust and clouds.  Similar imagery is also made using MODIS Polar orbiting satellites.  Shown below are the pink and yellow dust products using the MODIS Aqua satellite imagery at 2020 UTC.

Pink dust product using Aqua MODIS imagery at 2020 UTC on 16 January.

Yellow dust product using Aqua MODIS imagery at 2020 UTC on 16 January

We noted earlier that there was also snow in the background in some spots across the Plains, as well of course in the mountains.  The next set of imagery shows the CIRA snow/cloud (discriminates snow from clouds) and snow/cloud layer (further discrimination of the type of clouds, pinkish for generally higher ice clouds and yellow for generally lower water clouds).

Snow/cloud discriminator product using NPP VIIRS imagery at 1848 UTC on 16 January

Snow/cloud layer discriminator product using NPP VIIRS imagery at 1848 UTC on 16 January

Snow/cloud discriminator product using NPP VIIRS imagery at 2029 UTC on 16 January

The snow/cloud layer discriminator product uses the 1.38 micron “cirrus” band to isolate higher level ice clouds (an added step from the binary snow/cloud discriminator product).  An example of the cirrus imagery by itself is shown below for the 2020 UTC time.

Cirrus product using Aqua MODIS imagery at 2020 UTC on 16 January

Posted in Blowing Dust (Blue-light absorption technique), Blowing Dust Detection (Split-window technique), MODIS Snow/Cloud Discriminator | 1 Comment

Fog and Low Clouds in Eastern Colorado as seen with GeoColor and Day Night Band NPP VIIRS imagery on 20 Dec 2013

The Suomi NPP VIIRS Day/Night Band (DNB), which can use moonlight to produce visible-light imagery during the nighttime, offers a unique capability that is slated to continue on the JPSS constellation concurrent to the GOES-R era.  This presents intriguing potential for synergy between the DNB and Advanced Baseline Imager.  One can use the imagery just as visible imagery is currently used in the daytime, so there are many applications.  Here we show how fog and low clouds distinctly appear during the nighttime hours using the DNB imagery, shown below first on a larger scale and then zoomed in over Colorado.

DNB imagery over the western half of the CONUS at 0914 UTC on 20 December 2013.

DNB imagery centered over Colorado at 0914 UTC on 20 December 2013.

Lights from the various towns and cities are seen in the DNB imagery.  City lights are also a part of one of the earlier CIRA Proving Ground demonstration imagery known as GeoColor imagery.  GeoColor is intended to be a survey type imagery that has a seamless transition from night to day by combining different bands and background imagery.  The current version uses a static nightime background of city lights (though it will be possible to update to quasi-real time imagery using Polar satellites), as seen in the image below for the same time as the DNB images displayed above.  An added feature of the GeoColor imagery is the use of the 11-3.9 micron difference (the standard AWIPS fog product) to color low clouds and fog in a pinkish tone to highlight them from other clouds, as seen below.  One characteristic of the imagery that has been noticed during cases of fog is that there may be some information about the thickness and/or density of the fog by how much of the city lights appear through the fog layer, and it will be interesting to examine more DNB imagery in this regard.

GeoColor imagery over the western half of the CONUS at 0945 UTC on 20 December 2013.

Note how in the GeoColor imagery higher clouds appear in white tones, and we can see that high clouds extend across portions of eastern Colorado, covering the lower clouds and fog.  However, going back to the DNB imagery,  the cirrus barely shows in this imagery (as it would with visible imagery in the daytime) and we are therefore able to see the low clouds and fog more clearly.  This example shows how VIIRS and GOES-R could be used in synergy during the GOES-R era.

Posted in GeoColor Imagery, Uncategorized | 1 Comment

Orographic Cirrus of 18 December 2013

Orographic cirrus (i.e., mountain wave) clouds can have a significant influence on temperature forecasts, particularly during the cold season when a reduction in insolation can drastically affect temperatures during the daytime.

On December 18, 2013 the CIRA synthetic 4-km NSSL-WRF ARW and NAM-Nest initialized at 0000 UTC 18 December forecasted orographic cirrus downwind of the Front Range of Colorado during the early morning hours:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/18dec13_synthetic&image_width=1020&image_height=900

the synthetic NSSL WRF-ARW is shown on the left, while the synthetic NAM-Nest is shown on the right, the loop spans from 0900 UTC 18 December – 0300 UTC 19 December (9 to 27 hr forecast).  During the mid-day time period, the forecasts begin to diverge with the NSSL WRF-ARW showing a thinning out of the orographic cirrus while the NAM-Nest does not show this trend.  Both models indicate redevelopment of orographic cirrus in the evening hours.

The NWS Boulder forecast discussion issued at 4:49 AM MST 18 December highlighted the importance of orographic cirrus potentially limiting the daytime high temperature forecast, note the use of the CIRA synthetic imagery as a forecast tool:

SHORT TERM

MAIN QUESTION TODAY IS THE AMOUNT OF CLOUD COVER AND

ITS EFFECT ON TEMPERATURES. PLENTY OF MOISTURE UPSTREAM THOUGH

THERE IS SOME VARIABILITY. WITH NOT MUCH CHANGE IN THE WIND

PATTERN…EXPECT THE WAVE CLOUD COVERING THE PLAINS TO CHANGE

LITTLE TODAY WHILE THERE MAY BE SOME DECREASE IN THE HIGH CLOUDS

OVER THE MOUNTAINS. CIRA SIMULATED SATELLITE IMAGERY SHOWS A

PRETTY SOLID WAVE CLOUD PERSISTING DOWNSTREAM OF THE FRONT RANGE

THROUGH TONIGHT WITH POOR AGREEMENT ON THE TIMING OF ANY CLEARING

ELSEWHERE. SHOULD BE ENOUGH CLOUDS TO LIMIT TEMPERATURES…BUT THE

AIRMASS HAS ALSO WARMED A LITTLE SINCE YESTERDAY. WE WILL BE OFF

TO A WARM START…ALREADY IN THE 50S IN THE LOWER FOOTHILLS. UNDER

CLEAR SKIES IT WOULD PROBABLY BE 70 IN DENVER TODAY…SO THE

CURRENT MID 60S FORECAST IS PROBABLY STILL ALRIGHT.

An interesting way to view the influence of the mountain wave is a cross section (red line) oriented east-west across the Front Range as shown here:

The cross section of potential temperature from the NSSL WRF-ARW between 1300 UTC 18 December – 0300 UTC 19 December is shown below:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/18dec13_xsec_theta&image_width=1020&image_height=900

The mountain wave clearly shows up in the vertical through the depth of the troposphere.  Also note the sloped potential temperature lines do not make it all the way to the surface, which is consistent with the lack of high downslope winds for this event.

The verifying GOES IR imagery is shown here:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/18dec13_goes_ir&image_width=1020&image_height=900

Note the thinning out of orographic cirrus by the early afternoon hours, which seems to be more consistent with the NSSL WRF-ARW forecast.  This kind of monitoring GOES imagery versus synthetic imagery can assess how much confidence to put in one model forecast versus another.

The CIMSS blog has an entry on this event which includes views from polar orbiting satellites:

http://cimss.ssec.wisc.edu/goes/blog/archives/14607

Posted in Synthetic NSSL WRF-ARW Imagery | Leave a comment

Determining clouds from snow – an example from 5 Dec 2013

As winter continues to settle in across the nation and snow cover increases, an issue that arises is trying to see cloud cover over a snow pack during the daytime with visible satellite imagery, since both appear white.  Certainly looping the imagery can help although issues can still remain.  Snow cover can have a significant effect on the local weather, including influencing both maximum and minimum temperatures, so it is important to determine the status of snow on the ground.

There are various methods that can be used to help discriminate clouds from snow cover, requiring information from different channels that are not available on the current GOES satellites.  These channels are found on some of the Polar-orbiting satellites, and similar channels will be available when GOES-R is launched.  Here we show an example of the type of satellite imagery that will be available during the GOES-R era by utilizing channels from the MODIS sensors on board the Terra and Aqua Polar-orbiting satellites, and from the VIIRS sensors on the new Suomi NPP satellite.

The first image shown below is a visible image from the Suomi NPP satellite, in this case True Color Imagery where the background is natural color.  A mix of snow and clouds exists from the Rockies eastward across the Central and Northern Plains, but it is difficult to distinguish one from the other.

Suomi NPP true color visible image at 2016 UTC on 5 Dec 2013.

Next is a CIRA product known as Snow/Cloud Layer Discriminator imagery, in this case from the Suomi NPP satellite utilizing various channels from the VIIRS sensors (details on how this imagery is constructed can be found here.

CIRA snow/cloud layer discriminator image at 2016 UTC on 5 Dec 2013.

In the image above the colors are defined as follows: green = land (clear sky, devoid of snow cover), white/bluish-white = snow cover, yellow = low-level liquid-phase clouds, and orange/magenta = mid/high level ice phase clouds.  There is a significant amount of tuning that is required for the various colors to match the phenomenon, and in the image above in some areas the snow appears with an excessively bluish tone.  The next image shows the same CIRA snow/cloud layer discriminator product but from the MODIS sensors on the Terra Polar-orbiting satellite.

CIRA MODIS snow/cloud layer discriminator image from the Terra satellite at 1805 UTC on 5 Dec 2013.

Although the channels used are similar in the two images, there are some slight variations between the two satellites.  For the snow/cloud layer discriminator product the MODIS imagery has been well tuned so that the colors show the desired contrast.  The slight color differences for the snow between the MODIS and VIIRS images reflect that more fine tuning is needed for the newer VIIRS imagery.  When GOES-R is launched similar tuning may be necessary.

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Synthetic imagery for the 3 Dec 2013 fog/low cloud case

The previous blog entry discussed CIRA satellite imagery that can be useful in highlighting fog and low clouds.  These images utilize existing satellite imagery to create images that try to replicate those that will be available in the GOES-R era.  Another method to create GOES-R type imagery is to use output from a high-resolution model (in this case NSSL’s 4-km WRF-ARW model run at 0000 UTC) to create “synthetic” satellite imagery.  An advantage to synthetic imagery is the ability to replicate many of the bands that will be on GOES-R.  We also replicate satellite imagery that forecasters currently use, such as IR, so that they can determine how well the model actually does in comparison to real-time available imagery.  A number of forecasters have found synthetic imagery to be a useful way to visualize model output, much in the way model radar reflectivity is now widely used.

One of the synthetic images being generated by CIRA replicates the AWIPS fog product, and uses the 10.35 minus 3.9 µm difference to highlight fog and low clouds as blue. Higher level clouds appear as black.  The image shown below is a 12-h forecast valid at 1200 UTC on 3 Dec, the type highlighted in the earlier blog.

Synthetic "fog product" valid at 1200 UTC on 3 Dec.

Of course this synthetic image, like its real image counterpart available in AWIPS, does not in itself discriminate between low clouds and fog.  But the model provides output that does allow one to better determine areas of fog.  This is shown in the image below, where the blue represents areas in which the cloud liquid water content at the lowest model level is nonzero, a proxy for fog.

Same 12-h forecast but here isolating moisture in the lowest model level to determine fog from low clouds.

Comparison of the two images shows that some of the areas in blue in the first image was not fog but low clouds.  Another advantage to the image above is that areas of fog are shown beneath the higher clouds (for example across Missouri and eastern Iowa) that obscure the fog in the synthetic image that includes higher level cloudiness.

Posted in Synthetic NSSL WRF-ARW Imagery | Leave a comment

Widespread Fog East of the Rockies – 3 Dec 2013

Widespread fog and low clouds covered much of the nation east of the Rockies 0n the morning of 3 Dec in the moist airmass ahead of the developing western storm and strong cold front that has since pushed south.  Dense Fog Advisories were issued by many WFOs, as seen in the graphic below valid at 1324 UTC on 3 Dec.

NWS Watches and Warnings as of 1324 UTC on 3 Dec 2013

The surface weather map at 1300 UTC on 3 Dec is shown below.  A complex storm system is taking shape in the Rockies while an Arctic high pushes cold air southward into the Northern Plains.

Surface analysis and plot at 1300 UTC on 3 Dec 2013.

A closer look at the observations is given in the plot below.  In this plot visibility is given below the station circle, weather to the right, and ceiling height (feet, AGL) to the left. Note the large number of stations reported low visibilities due to fog.  East of the dense fog area was a huge area with more scattered fog reports but widespread low overcast conditions.

METAR station plot of weather, ceiling and visibility at 1200 UTC on 3 Dec.

CIRA has two types of overview imagery that make fog and low clouds easier to see, and both will be available in improved versions in the GOES-R era.  Below we see an example of GeoColor imagery, one version with night lights and the other without, both for 1145 UTC on 3 Dec.  In this imagery low clouds and fog appear in red/pink tones, while clouds or snow cover are white.  Much of North America east of the Rockies is covered by low clouds and fog, interrupted in the imagery in some areas by higher clouds.  GeoColor imagery is intended as a general overview type of satellite imagery.

In the GeoColor imagery all clouds other than low clouds (or fog) appear white.  Another type of imagery (called Low-cloud/fog imagery) is designed to highlight low clouds and fog in a whitish color both during the night and during the day, but also colors higher clouds thereby giving more information about them.  An image also for 1145 UTC is shown below.  Note that thin cirrus appears as black during nighttime imagery, and we see that there are areas of thin cirrus covering some of the regions of low clouds and fog.

CIRA Low-cloud/fog imagery for 1145 UTC on 3 Dec.

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October 17, 2012 fog over Wisconsin

Let’s examine the synthetic low cloud / fog product from the 4-km NSSL WRF-ARW model.  This is from the 0000 UTC 17 October run valid between 0900-1600 UTC 17 October:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/17oct12_syn_fog&image_width=1020&image_height=900

Low cloud / fog is depicted as blue in this color table, with mid- to high level clouds being black / dark grey.  Early in the loop, note the region of blue (low cloud / fog) in northern Wisconsin.  As the loop progresses, this region quickly becomes obscured by mid- to high level clouds that are moving eastward.  It’s unclear when this low cloud / fog is forecast to dissipate in northern Wisconsin due to the higher levels clouds obscuring what is happening at lower levels.

When you come across a situation such as this, one option to get around this issue is to use the NSSL WRF-ARW experimental fog product.  This is simply the model output of cloud liquid water at the lowest vertical level in the model.  Here is the loop from 0900-1800 UTC, with cloud liquid water depicted as blue:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/17oct12_exp_fog&image_width=1020&image_height=900

Fog can be inferred from the blue regions we observe in this loop.  We avoid the issue of obscuration of higher level clouds, and we may also discriminate between low cloud and fog (as forecast by the model).

Another option for fog identification is the GOES-R Fog / Low Stratus Product from CIMSS.  This product uses a blend of satellite imagery and 00 hour forecast model output (from the RAP, except it uses the GFS over oceans beyond the RAP domain)  to assign a probability of fog.  This differs from the previous experimental fog product above which is solely model output, run out to a longer forecast time.  The following loop is the GOES-R FLS product for IFR fog:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/17oct12_goes-r_fls&image_width=1020&image_height=900

The color bar is given as a percentage, so that greater percent probability of IFR fog exists in the orange to red colors.  The visibility (bottom number, miles) and ceiling (top number, hundreds of feet AGL) observations are also overlaid so that locations of fog correspond to the regions of low visibilities.  Note the regions of orange and red in northern Wisconsin indicating higher probabilities of fog which would cause IFR conditions, this closely corresponds to the observed fog from the observations.

For more detailed information on either the GOES-R fog / low stratus product, or the synthetic low cloud / fog product, see the training session from VISIT:

http://rammb.cira.colostate.edu/training/visit/training_sessions/

Posted in GOES Low Cloud / Fog Imagery, Synthetic NSSL WRF-ARW Imagery | Leave a comment

Synthetic low cloud / fog imagery to forecast stratus

The synthetic low cloud / fog product from the NSSL WRF-ARW model has a variety of forecasting applications.  One of those is forecasting the development of stratus clouds.

The NWS forecast office in Austin / San Antonio made use of this product for the above mentioned application on September 23:

AREA FORECAST DISCUSSION

NATIONAL WEATHER SERVICE AUSTIN/SAN ANTONIO TX

626 PM CDT SUN SEP 23 2012

AVIATION…

CONVECTION ALONG THE SEA-BREEZE BOUNDARY WILL REMAIN SOUTH OF KSSF AND KSAT AND WILL DISSIPATE AFTER SUNSET WITH THE LOSS OF DAYTIME HEATING. OTHERWISE THE CU FIELD THIS AFTERNOON IS AN INDICATION OF INCREASING LOW LEVEL GULF MOISTURE ACROSS SOUTH CENTRAL TEXAS. THE 18Z NAM X-SECTIONS DEPICT GOOD MOISTURE BELOW 925MB AT KSAT AND KSSF BUT SHALLOWER AT KAUS AND SOMEWHAT DRIER AT KDRT. THE 12Z CIRA WRF SIMULATED FOG/LOW CLOUD PRODUCT IS VERY BULLISH ON STRATUS FORMATION OVERNIGHT. WE HAVE HAD GOOD RESULTS WITH THIS EXPERIMENTAL PRODUCT AND THE TERMINAL FCSTS WILL BE BASED ON ITS SOLUTION. MVFR CIGS WILL REACH KSSF AROUND 09Z…KSAT AT 0930Z AND KAUS BY 12Z. THE STRATUS WILL ALSO SPREAD WESTWARD REACHING KDRT BY 13Z. THE STRATUS WILL LIFT AND MIX OUT WITH VFR CONDITIONS PREVAILING BY 16Z.

Here is the synthetic low cloud / fog product that is the discussed above:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/24sep12_syn_fog&image_width=1020&image_height=730

In this color table, low cloud / fog shows up as blue.  The expanding blue region over southern and central Texas corresponds to the model forecasting the development of low cloud / fog.

As verifying observations, we will make use of the GOES low cloud / fog product with corresponding visibility (bottom number, miles) and ceiling (top number, hundreds of feet AGL) observations:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/24sep12_sw_albedo&image_width=1020&image_height=730

In this color table, low cloud / fog corresponds to the grey / dull white region in south / central Texas.  The stratus clouds were forecast over approximately the same area in Texas that was forecast by the model, and dissipation commencing at about the same time (around 16 Z)

The real-time imagery described above can be found on the GOES-R Proving Ground Real-time Products page.

Posted in Synthetic NSSL WRF-ARW Imagery | Leave a comment

Synthetic Satellite Imagery evaluated at SPC

As part of NOAA’s Hazardous Weather Testbed Spring Experiment at the Storm Prediction Center, CIRA is delivering 3 synthetic imagery products to be evaluated in the Experimental Warning Portion of the experiment in their AWIPS-II system: 6.95 micrometers, 10.35 micrometers, and the 10.35 – 12.3 micrometer difference product.  Chris Siewert is hosting a separate blog and regularly adding posts with details on how the products are being evaluated.  Those entries can be found here: http://goesrhwt.blogspot.com/search/label/Simulated%20Satellite%20Imagery

Posted in Synthetic NSSL WRF-ARW Imagery | Leave a comment

ORI product for 18-20 December 2010 massive California rain event

A period of extremely heavy rain and massive higher elevation snow hit California and other portions of the West during mid-December 2010.  Here we take a look at the ORI product for a portion of this storm, concentrating on Central and then Southern California.  The ORI (for Orographic Rain Index) product is designed to indicate to forecasters where there is short-term (0-3 hours) potential for heavy orographic rain. The product has a horizontal resolution of approximately 1 km.

Three data sources are used to create the ORI product:

  1. Blended Total Precipitable Water (TPW) from CIRA, which indicates the strength and location of atmospheric rivers impinging on the U.S. West Coast,
  2. GFS 850 mb winds (V), which are used to advect the water vapor to a forecast time (every 3 hours), and
  3. USGS Global 30 Arc-Second Elevation Data (GTOPO30) terrain elevations (H) (horizontal resolution of approximately 1 km).

The CIRA TPW product is derived from water vapor measurements from various non-GOES sensors/satellites to determine Total Precipitable Water.  In the future GOES-R will provide these measurements, so this is why the ORI product represents an application that will be available in the GOES-R era.  More information on the ORI product can be found in the CIRA ORI Product Description, which is available at http://rammb.cira.colostate.edu/research/goes-r/proving_ground/cira_product_list/.

This event was a classic “atmospheric river” type with a long fetch of Pacific moisture aimed at California.  An IR image shown below in Figure 1 near the beginning of the event illustrates this extensive moisture plume, with the first wave of the event about to come onshore.

Figure 1.  IR image overlaid with a GFS 500 mb analysis at 0000 UTC on 18 Dec 2010.

As noted earlier, the precipitation totals for this event were quite large.  The 7-day accumulated precipitation estimate shown in Figure 2 illustrates this, with a large area in the 10 to 20 inch range.  Topography played a huge role, as it typically does in such events.  Details of the terrain for the scale of some of the images to be shown are shown in Figure 3.

Figure 2.  Estimated 7-day total precipitation ending 1200 UTC 20 Dec 2010.

Figure 3.  Details of the terrain are shown in these two images.  The radar and ORI images shown below are on the scale of the zoomed in image on the right.

The next few images show a demonstrate the ORI product as the first wave of heavy precipitation moved inland for four different times from 0600 UTC through 1500 UTC. All of the images are taken from an AWIPS display localized for the Monterey WFO.   For each time a comparison is made between the ORI product and what the radar reflectivity looked like for an area centered on Central California.  The bottom images for each time are zoomed into the area that is depicted on the right side of Figure 3.  The ORI image is shown in the lower left panel, with the same ORI field combined with a topography image next to it.  For the 0900 UTC time an additional radar image is shown on this same scale.

As forecasters know, radar can have a tough time resolving precipitation in regions of complex topography.  The beauty of the ORI product is that it focuses specifically on topography and how it influences the impinging moisture field, as determined by the TPW, and as influenced by the flow driving this moisture into the higher terrain.  This is nicely seen in the images below.  One of the downsides to the ORI product from the forecaster standpoint is that the ORI value is an index and not a precipitation measurement.  Further experience by forecasters with the ORI product will help to determine how the ORI values relate to significant precipitation amounts that will help to improve its usefulness for nowcasting.  As discussed in the ORI Product Description, some guidance on ORI values based roughly on the work of Nieman et al. 2008 (J. Hydrometeorology, 9, 22-47) are: 50 kg s-1 m-1 (the units of ORI) are set as a threshold below which no rain is likely, while a value of 250 kg s-1 m-1 which definitely deserves the forecaster’s attention. (Maximum values are probably in the 500 kg s-1 m-1range.)  In the example below, ORI increases to a value above 200 in the region highlighted by the white oval by 0900 UTC, then falls off as the heavier precipitation moves further inland.

Figure 4.  ORI comparison for 0600 UTC on 18 December.  The scale of the two bottom images are the same as the zoomed in image shown in Figure 3.

Figure 5.  ORI comparison for 0900 UTC on 18 December.

Figure 6.  ORI comparison for 1200 UTC on 18 December.

Figure 7.  ORI comparison for 1500 UTC on 18 December.

Further details on this case will be forthcoming, but it is hoped that additional examples can be added to the blog from cases yet to come as the rainy season (finally) gets under way.

Posted in Orographic Rain Index (ORI) | Leave a comment